EOVSA Wiki - User contributions [en]

Owens Valley Solar Arrays

2025-10-29T17:06:24Z

Binchen: /* OVSA Scientist on Duty */

<big>Owens Valley Solar Arrays (OVSA) is a university-led radio facility dedicated to solar astrophysics and space weather research. Located in the Owens Valley Radio Observatory (OVRO) near Big Pine, California, the operations of OVSA include the Expanded Owens Valley Solar Array (EOVSA) observing in the microwave regime (1-18 GHz), as well as the solar and space weather aspects of the newly commissioned Long Wavelength Array at the Owens Valley Radio Observatory (OVRO-LWA), which observes in the meter-decameter wavelength regime (13-87 MHz). Please refer to [https://ovsa.njit.edu/ our home page] for more general descriptions of the facility. This wiki serves as the site for OVSA documentation. </big>

{| class="wikitable" style="border: none;"
|-
| ''Operation of OVSA is supported by the National Science Foundation under Grant AGS-2436999. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.''
| [[File:NSF.jpg|70px]]
|}

== Latest OVSA Science Highlights ==
[[OVSA Science Highlight No. 6: Detection of Radio Gyroresonance Emission from a CME]]
[[File:cme_20240309.jpeg|left|100px]]
[https://arxiv.org/abs/2509.16453 This study] reports the first possible detection of thermal gyroresonance emission from a CME. This breakthrough offers a new potential method for measuring the magnetic field of CMEs. [Contributed by Surajit Mondal (New Jersey Institute of Technology); Edited by B. Chen. Posted on September 26, 2025.]

<div style="clear: both;"></div>

[[OVSA Science Highlight No. 5: Is CME's Magnetic Flux Conserved?]]
[[File:cme_mfr.jpeg|left|100px]]
According to [https://iopscience.iop.org/article/10.3847/2041-8213/adfa71 this study], the answer is "probably yes." The conclusion is made by using ultrabroadband radio imaging spectroscopy to derive the magnetic field evolution of an erupting CME from the low to middle corona. [Contributed by Xingyao Chen (New Jersey Institute of Technology); Edited by B. Chen. Posted on September 19, 2025.]

<div style="clear: both;"></div>

[[OVSA Science Highlight No. 4: When the Sun Meets the Crab]]
[[File:crab_solar_conjunction.jpeg|left|100px]]
When the Crab Nebula passes behind the Sun each June, radio telescopes can catch its distorted signals, providing a rare way to probe turbulence in the Sun’s extended atmosphere out to more than 10 solar radii. [Contributed by Peijin Zhang (New Jersey Institute of Technology); Edited by B. Chen. Posted on September 11, 2025.]

<div style="clear: both;"></div>

[[OVSA Science Highlight No. 3: The First EOVSA "Cold" Solar Flare]]
[[File:cold_flare.jpeg|left|100px]]
[https://iopscience.iop.org/article/10.3847/1538-4357/ade983 This study] takes advantage of EOVSA's microwave imaging spectroscopy capability and multi-wavelength observations to measure the coronal magnetic field and track the flare energy partitioning. The results show ample magnetic free energy to drive efficient electron acceleration, with the energy deposition of nonthermal electrons alone accounting for the observed thermal response, reinforcing cold flares as clean cases of particle-driven heating. [Contributed by Gregory Fleishman (New Jersey Institute of Technology); Edited by B. Chen. Posted on August 20, 2025.]

<div style="clear: both;"></div>

[[OVSA Science Highlight No. 2: Two Phases of Impulsive SEP Acceleration]]
[[File:SEP_illustration_gemini.jpeg|left|100px]]
[https://iopscience.iop.org/article/10.3847/1538-4357/adbdd0 M. Wang et al.] analyze a solar energetic particle (SEP) event associated with an eruptive X-class flare and found two distinct impulsive SEP acceleration phases. They are suggested to link to different magnetic reconnection regimes during the eruption, which govern the timing and energy of particles released into interplanetary space. [Contributed by Meiqi Wang (New Jersey Institute of Technology); Edited by B. Chen. Posted on August 19, 2025.]

<div style="clear: both;"></div>

[[OVSA Science Highlight No. 1: Microwave Precursor of a Major Solar Eruption]]
[[File:solar_eruption_nasa.jpeg|left|100px]]
A study by [https://iopscience.iop.org/article/10.3847/2041-8213/adf063 Y. Kou et al.] presents the first spatially resolved microwave imaging spectroscopy of the precursor phase of a major solar eruption. The findings reveal that thermal electron emissions dominate during the slow-rise phase, supporting a scenario of moderate magnetic reconnection prior to the flare’s impulsive onset. [Contributed by Yuankun Kou (Nanjing University); Edited by B. Chen. Posted on August 2, 2025.]

<div style="clear: both;"></div>

We welcome contributions at all times. Please refer to the [[OVSA Science Highlights]] page for author guidelines and a complete list of highlights.

<div style="clear: both;"></div>

== OVSA Publications ==
Our collection of publications that utilize OVSA data is available at [https://ui.adsabs.harvard.edu/public-libraries/eQ7HfPkySqydu-B8BCt6QQ this NASA/ADS Library]. If you have a paper that is missing from this library, please email Bin Chen (bin.chen [at] njit.edu).


== EOVSA Flare List ==

* [https://ovsa.njit.edu/flarelist Query EOVSA Flare list]
* List of EOVSA flares in separate years: [[2025]], [[2024]], [[2023]], [[2022]], [[2021]], [[2020]], [[2019]], [[2017]]

== OVSA Observing ==

=== OVSA Weekly Observing Reports ===
* 2025: [https://drive.google.com/file/d/1NLJpfehI7XiyNQc_9L69H9xrXn_LsCQM/view?usp=drive_link Aug 26-Sept 1], [https://drive.google.com/file/d/1QiD9rk_DocXT1F3aRl3L49AAyaNaR9d1/view?usp=drive_link Sept 2-8], [https://drive.google.com/file/d/1O2oGCAAnBX4YOmbWsra14zPxk2t7CQXn/view?usp=drive_link Sept 9-15], [https://drive.google.com/file/d/1C-CF_OW8EqQflTPzceRzAyX3cRq8hKJ6/view?usp=drive_link Sept 16-22], [https://drive.google.com/file/d/14ci0XpFu-kqPbcoPliUjnDNOHAoXi1vH/view?usp=drive_link Sept 23-29]

=== OVSA Scientist on Duty ===
* Scientist on Duty (SoD): OVSA team members take turns and serve as a SoD to work with our onsite observatory staff on day-to-day observing. They are also responsible for monitoring solar activities and ensuring that the data we collect is of high quality.
* SoD observing logs ([https://drive.google.com/drive/folders/1q6-0Z9B0CPFutuTqzmeheEUSJM3tEL2o?usp=drive_link directory to all logs and weekly reports]):
** 2024: [https://docs.google.com/document/d/1QDWw5y4HpcE7CSpzXwftMqQT4FDgNJj-6fRrgWrqdug/edit?usp=sharing May (and before that)], [https://docs.google.com/document/d/1Rh2gYBV2E454xVYEv8jx5IXKd1N2Z05ns4dhI2XCE08/edit?usp=sharing June], [https://docs.google.com/document/d/1beUpp6rgwjqSxKbuHzXIR9hhPrGyi0j-SjtEIeav9Vg/edit?usp=sharing July], [https://docs.google.com/document/d/1pSzUXW5gd-4cZAR-gglTUVM_J2UHMa4wYJ2AzD4cdEo/edit?usp=sharing August], [https://docs.google.com/document/d/18pArAP0kRDhXHbty_y3TtrygmWkC2oLn-UD7njIpRIo/edit?usp=sharing September], [https://docs.google.com/document/d/1Qt6vhrqPAOG7W5Y_tLiod_QgNR1FDyzRxQcg6_oJQd4/edit?usp=sharing October], [https://docs.google.com/document/d/1pv9-Wne80FCrg0J5BkjOafmof_s3jlnc9HwyzWkIBfU/edit?usp=sharing November], [https://docs.google.com/document/d/1O5svOVwQZbUON1GMR_8nBR5LAL0M8RM2_zWW4oeBiLk/edit?usp=sharing December]
** 2025: [https://docs.google.com/document/d/1pUdSRyWgQa2py1PSLa3CKs_DDqL_SOgx6MMIp4cPnpk/edit?usp=sharing January], [https://docs.google.com/document/d/18cnIAaeM8UBiYPtsQn7g6TM8mjr57blSoY9l-6ShhwQ/edit?usp=sharing February], [https://docs.google.com/document/d/1k60i7nabWltnU38I7fGS2uq2-FUe5TMAKcM1BeLIRdY/edit?usp=sharing March], [https://docs.google.com/document/d/1CMaXBtA1ULNFbzuawYirP913A6dTa68cbYk2a7knirI/edit?usp=sharing April], [https://docs.google.com/document/d/13Kr8lYfFN9bzgFvCJi6nBUxbQHa3_eTgfjwaCUn3vCs/edit?tab=t.0 May], [https://docs.google.com/document/d/1ptGvQiB6SPgzJ-I6IgJ4bKK-3GPK-4LBpq7BG6sFPSg/edit?usp=sharing June], [https://docs.google.com/document/d/1XrOonOdwrkSDSWT2CwvzIaw7aRxBA4Sba1GCMRmkDZk/edit?usp=sharing July], [https://docs.google.com/document/d/1MzKkL8cPaBLNDOuws4U0ATuTN7kVaaeX4dUp0cga3vo/edit?usp=sharing August], [https://docs.google.com/document/d/14JHnHLZiDTqtK_cmaHgRevKksHuqijBQcMo1zcrz98k/edit?usp=sharing September], [https://docs.google.com/document/d/1RypoU6RtXVIdak_ESgabEK1Gp8XG7Tok2kHhPNZ3G4g/edit?usp=sharing October]
* SoD instructions:
** Daily routines: see [https://docs.google.com/document/d/1_iGnMRRrvb85Z0vT8-LzgQmCOKDSATEuQ0vTsn2C-dc/edit?usp=sharing SoD Routines] for detailed instructions.
** Instructions for [[making quick-look flare spectrograms and movies]]

=== EOVSA Observing Log ===
[[2016 November]]; [[2016 December| December]]

[[2017 January]]; [[2017 February | February]]; [[2017 March | March]]; [[2017 April | April]]; [[2017 May | May]]; [[2017 June | June]];
[[2017 July | July]]; [[2017 August | August]]; [[2017 September | September]]; [[2017 October | October]]; [[2017 November | November]]; [[2017 December | December]]

[[2018 January]]; [[2018 February | February]]; [[2018 March | March]]; [[2018 April | April]]; [[2018 May | May]]; [[2018 June | June]];
[[2018 July | July]]; [[2018 August | August]]; [[2018 September | September]]; [[2018 October | October]]; [[2018 November | November]]; [[2018 December | December]]

[[2019 January]]; [[2019 February | February]]; [[2019 March | March]]; [[2019 April | April]]; [[2019 May | May]]; [[2019 June | June]];
[[2019 July | July]]; [[2019 August | August]]; [[2019 September | September]]; [[2019 October | October]]; [[2019 November | November]]; [[2019 December | December]]

[[2020 January]]; [[2020 February | February]]; [[2020 March | March]]; [[2020 April | April]]; [[2020 May | May]]; [[2020 June | June]];
[[2020 July | July]]; [[2020 August | August]]; [[2020 September | September]]; [[2020 October | October]]; [[2020 November | November]]; [[2020 December | December]]

[[2021 January]]; [[2021 February | February]]; [[2021 March | March]]; [[2021 April | April]]; [[2021 May | May]]; [[2021 June | June]];
[[2021 July | July]]; [[2021 August | August]]; [[2021 September | September]]; [[2021 October | October]]; [[2021 November | November]]; [[2021 December | December]]

[[2022 SQL Outage]]

[[2023 January]]; [[2023 February | February]]; [[2023 March | March]]; [[2023 April | April]]; [[2023 May | May]]; [[2023 June | June]];
[[2023 July | July]]; [[2023 August | August]]; [[2023 September | September]]; [[2023 October | October]]; [[2023 November | November]]; [[2023 December | December]]

[[2024 January]]; [[2024 February | February]]; [[2024 March | March]]; [[2024 April | April]]; [[2024 May |May]]; [[2024 June | June]]; [[2024 July | July]]; [[2024 August | August]];
[[2024 September | September]]; [[2024 October | October]]; [[2024 November | November]]; [[2024 December | December]]

[[2025 January]]; [[2025 February | February]]; [[2025 March | March]]; [[2025 April | April]]; [[2025 May |May]]; [[2025 June | June]]; [[2025 July | July]]; [[2025 August | August]];
[[2025 September | September]]; [[2025 October | October]]; [[2025 November | November]]; [[2025 December | December]]

== Using OVSA Data ==
* <big>[[EOVSA Data Products]]</big>: An introduction to standard EOVSA spectrogram and spectral image products with example scripts for reading and plotting.
* <big>[[OVRO-LWA Solar Data Products]]</big>: An introduction to OVRO-LWA solar spectrogram and spectral image products with example scripts for reading and plotting.
* <big>[[OVSA Data Policy]]</big>: Policy for using OVSA data products.
* <big>Analysis Software</big>: These are for in-depth use of EOVSA data (from calibrated visibilities) and tools for quantitative analysis.
** [https://github.com/suncasa/suncasa SunCASA] A wrapper around [https://casa.nrao.edu/ CASA (the Common Astronomy Software Applications package)] for synthesis imaging and visualizing solar spectral imaging data. CASA is one of the leading software tool for "supporting the data post-processing needs of the next generation of radio astronomical telescopes such as ALMA and VLA", an international effort led by the [https://public.nrao.edu/ National Radio Astronomy Observatory]. The current version of CASA uses Python (2.7) interface. More information about CASA can be found on [https://casa.nrao.edu/ NRAO's CASA website ]. Note, CASA is available ONLY on UNIX-BASED PLATFORMS (and therefore, so is SunCASA).
** [https://github.com/Gelu-Nita/GSFIT GSFIT] A IDL-widget(GUI)-based spectral fitting package called gsfit, which provides a user-friendly display of EOVSA image cubes and an interface to fast fitting codes (via platform-dependent shared-object libraries).
** [https://github.com/suncasa/pygsfit pyGSFIT] A Python-widget(pyQT)-based spectral fitting package, which provides a user-friendly display of EOVSA image cubes, spatially resolved spectra, and an interface to scipy-based fitting codes.
** [[Spectrogram Software]]
** [[Mapping Software]]
* <big>Data Analysis Guides (for those who start from raw data) </big>






**[[Tohban Guide to Self Calibration and Imaging for EOVSA]] Step-to-step guide for manually making images from raw visibility data.
**[[EOVSA flare pipeline]] Description of the EOVSA flare pipeline and tutorial for running it to produce quicklook images.



* <big>EOVSA Modeling Guide</big>
**[[GX Simulator]]

* Other helpful links
** [https://casaguides.nrao.edu CASA Guides]
** [http://www.lmsal.com/solarsoft/ SolarSoft IDL]
** [http://www.atnf.csiro.au/computing/software/miriad/userguide/userhtml.html Miriad Guides]
** [https://sites.google.com/site/fgscodes/ Fast Gyrosynchrotron Codes (Alexey Kuznetsov's website)]
** [[Basic GitHub Tutorial]]


* <big>[[Full Disk Simulations]]</big>
* <big>[[All-Day Synthesis Issues]]</big>
* <big>[[Analyzing Pre-2017 Data]]</big>
* <big>[[Fixing Pipeline Problems pre-2021-Feb-07]]</big>

== EOVSA Documentation ==

* <big>General</big>
** [[Downconversion and Frequency Tuning]]
** [[Dealing with Radio Frequency Interference]]
** [[Switching between 200 MHz and 300 MHz Correlator]]
** [[Observing in "Fast" Mode]]

* <big>Computer-Network</big>
** [[Computing Systems]]
** [[Network]]

* <big>Control System</big>
** [[27-m Antenna Commands]]
** [[Schedule Commands]]
** [[Control Commands]]
** [[Attenuation and Level Control]]

* <big>Hardware</big>
** [[Hardware Overview]]
** [[2.1-m Antennas]]
** [[27-m Antennas]]

* <big>System Software</big>
** [[Calibration Database]]
** [[Stateframe Database]]
** [[Database Maintenance]]
** [[Create CASA measurement sets]]

* <big>Calibration</big>
**[[Calibration Overview]]
**[[Pointing Calibration]]
**[[Total Power Calibration]]
**[[System Gain Calibration]]
**[[Antenna Position]] (Baseline Calibration)
**[[Reference Gain Calibration]]
**[[Daily Gain Calibration]]
**[[Delay Calibration]]
**[[Bandpass Calibration]]
**[[Polarization Calibration]]
**[[Calibrator Survey]]
**[[Practical Calibration Tutorial]]

* <big>[[Starburst]]</big>

== EOVSA System Software ==

* LabVIEW software
* Python code [https://github.com/dgary50/eovsa Github repository]
* [[Python3 Code Installation]]

==OVRO-LWA Solar-Dedicated Spectroscopic Imager==
The OVRO-LWA (Owens Valley Radio Observatory Long Wavelength Array) has recently been upgraded to include a solar-dedicated beam and two solar imaging modes (slow visibilities of 352 antennas with a 10-s cadence, and fast visibilities of 48 antennas with a 0.1-s cadence). The large collecting area and excellent calibration provide unprecedented high-sensitivity imaging of the quiet Sun and bursts. The array is currently in commissioning and observations are not yet continuous, but they are becoming more so. See the daily realtime data at http://ovsa.njit.edu/status.php for '''real-time display of the spectrogram and a selection of images''', both updated on a 1-min cadence.

===Solar-Dedicated Modes===
* Beamformer: The OVRO-LWA beamformer uses the 256 antennas in the core region to form a synthesized beam of more than 1 degree in size that tracks the Sun from sunrise to sunset. This permits a continuous record of the full-Stokes total flux (without spatial resolution) of the Sun (a dynamic spectrum) with 24 kHz frequency resolution (3072 frequencies from 13.4-86.9 MHz) and as low as 1 ms time resolution.

* Standard Interferometric Imaging (also known as "Slow Visibilities"): In this mode, the entire 352-element array is interferometrically correlated to provide visibilities for imaging at all 3072 frequencies at 10-s time resolution. This is ideal for imaging quiet Sun and slowly-varying emission such as coronal mass ejections and active region variability.

* Bursty Interferometric Imaging (also known as "Fast Visibilities"): In this mode, a subset of 48 antennas (chosen to include mainly outer antennas to maintain good spatial resolution) is interferometrically correlated to provide visibilities for imaging at 768 frequencies (96 kHz frequency resolution) at 0.1-s time resolution. This is ideal for imaging rapidly varying emission such as type II and type III bursts as well as many other solar spectral fine structures.

===Data Access===
* OVRO-LWA solar data release v1.0 is available! Please refer to the [[OVRO-LWA Data Products]] page for more information.

===OVRO-LWA Operation Notes===

[[OVRO-LWA Operation Notes]]

== Tohbans ==

[[Trouble Shooting Guide]]

[[Tohban Records]]

[[Owen's Notes]]

[[Caius' Notes]]

[[Tohban EOVSA Imaging Tutorial A-Z]]

[[Tohban OVRO-LWA Imaging Tutorial]]

[[Tohban Guide to Self Calibration and Imaging for EOVSA]]

[[Guide to Upgrade SolarSoft(SSW)]]

[[Star Pointing Notes]]

== VLA Flare List and Publications ==
See [http://www.ovsa.njit.edu/wiki/index.php/VLA_Data_Survey#List_of_Jansky_VLA_Solar_Observations this link] for a list of flare observations made by the [https://science.nrao.edu/facilities/vla/ Karl G. Jansky Very Large Array] (VLA). Below is a partial list of publications that utilize VLA solar data (see also [https://ui.adsabs.harvard.edu/public-libraries/ZwbjpLo9RS-viufWEoQ95Q this NASA/ADS Library]).
* [https://ui.adsabs.harvard.edu/abs/2022ApJ...940..137L/abstract Luo et al. (2022), ApJ, 940, 137] ''Multiple Regions of Nonthermal Quasiperiodic Pulsations during the Impulsive Phase of a Solar Flare''
* [https://ui.adsabs.harvard.edu/abs/2021ApJ...922..134B/abstract Battaglia et al. (2021), ApJ, 922, 134] ''Multiple Electron Acceleration Instances during a Series of Solar Microflares Observed Simultaneously at X-Rays and Microwaves''
* [https://ui.adsabs.harvard.edu/abs/2021ApJ...911....4L/abstract Luo et al. (2021), ApJ, 911, 4] ''Radio Spectral Imaging of an M8.4 Eruptive Solar Flare: Possible Evidence of a Termination Shock''
* [https://ui.adsabs.harvard.edu/abs/2021ApJ...910...40Z/abstract Zhang et al. (2021), ApJ, 910, 40] ''Multiwavelength Observations of the Formation and Eruption of a Complex Filament''
* [https://ui.adsabs.harvard.edu/abs/2020ApJ...904...94S/abstract Sharma et al. (2020), ApJ, 904, 94] ''Radio and X-Ray Observations of Short-lived Episodes of Electron Acceleration in a Solar Microflare''
* [https://ui.adsabs.harvard.edu/abs/2019ApJ...884...63C/abstract Chen et al. (2019), ApJ, 884, 63] ''Radio Spectroscopic Imaging of a Solar Flare Termination Shock: Split-band Feature as Evidence for Shock Compression''
* [https://ui.adsabs.harvard.edu/abs/2019ApJ...872...71Y/abstract Yu & Chen (2019), ApJ, 872, 71] ''Possible Detection of Subsecond-period Propagating Magnetohydrodynamics Waves in Post-reconnection Magnetic Loops during a Two-ribbon Solar Flare''
* [https://ui.adsabs.harvard.edu/abs/2018ApJ...866...62C/abstract Chen et al. (2018), ApJ, 866, 62] ''Magnetic Reconnection Null Points as the Origin of Semirelativistic Electron Beams in a Solar Jet
''
* [https://ui.adsabs.harvard.edu/abs/2017ApJ...848...77W/abstract Wang et al. (2016), ApJ, 848, 77] ''Dynamic Spectral Imaging of Decimetric Fiber Bursts in an Eruptive Solar Flare''
* [https://ui.adsabs.harvard.edu/abs/2015Sci...350.1238C/abstract Chen et al. (2015), Science, 350, 1238] ''Particle acceleration by a solar flare termination shock''
* [https://ui.adsabs.harvard.edu/abs/2014ApJ...794..149C/abstract Chen et al. (2014), ApJ, 794, 149] ''Direct Evidence of an Eruptive, Filament-hosting Magnetic Flux Rope Leading to a Fast Solar Coronal Mass Ejection''
* [https://ui.adsabs.harvard.edu/abs/2013ApJ...763L..21C/abstract Chen et al. (2013), ApJL, 763, 21] ''Tracing Electron Beams in the Sun's Corona with Radio Dynamic Imaging Spectroscopy''

==Radio Data from Around The Heliosphere==
* [http://ovsa.njit.edu//wiki/index.php/Radio_Data_from_Around_the_World#Radio_Data_Access '' Radio Data '']

==Radio Astronomy Lecture Notes==
Here is a link to the [[Radio Astronomy Lecture Notes]] adapted from the Phys728: Radio Astronomy graduate-level course Prof. Dale Gary taught at NJIT until Spring 2019.

Owens Valley Solar Arrays

2025-09-19T13:33:44Z

Binchen: /* Latest OVSA Science Highlights */

<big>Owens Valley Solar Arrays (OVSA) is a university-led radio facility dedicated to solar astrophysics and space weather research. Located in the Owens Valley Radio Observatory (OVRO) near Big Pine, California, the operations of OVSA include the Expanded Owens Valley Solar Array (EOVSA) observing in the microwave regime (1-18 GHz), as well as the solar and space weather aspects of the newly commissioned Long Wavelength Array at the Owens Valley Radio Observatory (OVRO-LWA), which observes in the meter-decameter wavelength regime (13-87 MHz). Please refer to [https://ovsa.njit.edu/ our home page] for more general descriptions of the facility. This wiki serves as the site for OVSA documentation. </big>

{| class="wikitable" style="border: none;"
|-
| ''Operation of OVSA is supported by the National Science Foundation under Grant AGS-2436999. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.''
| [[File:NSF.jpg|70px]]
|}

== Latest OVSA Science Highlights ==
[[OVSA Science Highlight No. 5: Is CME's Magnetic Flux Conserved?]]
[[File:cme_mfr.jpeg|left|100px]]
According to [https://iopscience.iop.org/article/10.3847/2041-8213/adfa71 this study], which uses ultrabroadband radio imaging spectroscopy to track the magnetic field evolution of an erupting CME from the low to middle corona, the answer is "probably yes." [Contributed by Xingyao Chen (New Jersey Institute of Technology); Edited by B. Chen. Posted on September 19, 2025.]

<div style="clear: both;"></div>

[[OVSA Science Highlight No. 4: When the Sun Meets the Crab]]
[[File:crab_solar_conjunction.jpeg|left|100px]]
When the Crab Nebula passes behind the Sun each June, radio telescopes can catch its distorted signals, providing a rare way to probe turbulence in the Sun’s extended atmosphere out to more than 10 solar radii. [Contributed by Peijin Zhang (New Jersey Institute of Technology); Edited by B. Chen. Posted on September 11, 2025.]

<div style="clear: both;"></div>

[[OVSA Science Highlight No. 3: The First EOVSA "Cold" Solar Flare]]
[[File:cold_flare.jpeg|left|100px]]
[https://iopscience.iop.org/article/10.3847/1538-4357/ade983 This study] takes advantage of EOVSA's microwave imaging spectroscopy capability and multi-wavelength observations to measure the coronal magnetic field and track the flare energy partitioning. The results show ample magnetic free energy to drive efficient electron acceleration, with the energy deposition of nonthermal electrons alone accounting for the observed thermal response, reinforcing cold flares as clean cases of particle-driven heating. [Contributed by Gregory Fleishman (New Jersey Institute of Technology); Edited by B. Chen. Posted on August 20, 2025.]

<div style="clear: both;"></div>

[[OVSA Science Highlight No. 2: Two Phases of Impulsive SEP Acceleration]]
[[File:SEP_illustration_gemini.jpeg|left|100px]]
[https://iopscience.iop.org/article/10.3847/1538-4357/adbdd0 M. Wang et al.] analyze a solar energetic particle (SEP) event associated with an eruptive X-class flare and found two distinct impulsive SEP acceleration phases. They are suggested to link to different magnetic reconnection regimes during the eruption, which govern the timing and energy of particles released into interplanetary space. [Contributed by Meiqi Wang (New Jersey Institute of Technology); Edited by B. Chen. Posted on August 19, 2025.]

<div style="clear: both;"></div>

[[OVSA Science Highlight No. 1: Microwave Precursor of a Major Solar Eruption]]
[[File:solar_eruption_nasa.jpeg|left|100px]]
A study by [https://iopscience.iop.org/article/10.3847/2041-8213/adf063 Y. Kou et al.] presents the first spatially resolved microwave imaging spectroscopy of the precursor phase of a major solar eruption. The findings reveal that thermal electron emissions dominate during the slow-rise phase, supporting a scenario of moderate magnetic reconnection prior to the flare’s impulsive onset. [Contributed by Yuankun Kou (Nanjing University); Edited by B. Chen. Posted on August 2, 2025.]

<div style="clear: both;"></div>

We welcome contributions at all times. Please refer to the [[OVSA Science Highlights]] page for guidelines and a complete list of highlights.

<div style="clear: both;"></div>

== OVSA Publications ==
Our collection of publications that utilize OVSA data is available at [https://ui.adsabs.harvard.edu/public-libraries/eQ7HfPkySqydu-B8BCt6QQ this NASA/ADS Library]. If you have a paper that is missing from this library, please email Bin Chen (bin.chen [at] njit.edu).


== EOVSA Flare List ==

* [https://ovsa.njit.edu/flarelist Query EOVSA Flare list]
* List of EOVSA flares in separate years: [[2025]], [[2024]], [[2023]], [[2022]], [[2021]], [[2020]], [[2019]], [[2017]]

== Using OVSA Data ==
* <big>[[EOVSA Data Products]]</big>: An introduction to standard EOVSA spectrogram and spectral image products with example scripts for reading and plotting.
* <big>[[OVRO-LWA Solar Data Products]]</big>: An introduction to OVRO-LWA solar spectrogram and spectral image products with example scripts for reading and plotting.
* <big>[[OVSA Data Policy]]</big>: Policy for using OVSA data products.
* <big>Analysis Software</big>: These are for in-depth use of EOVSA data (from calibrated visibilities) and tools for quantitative analysis.
** [https://github.com/suncasa/suncasa SunCASA] A wrapper around [https://casa.nrao.edu/ CASA (the Common Astronomy Software Applications package)] for synthesis imaging and visualizing solar spectral imaging data. CASA is one of the leading software tool for "supporting the data post-processing needs of the next generation of radio astronomical telescopes such as ALMA and VLA", an international effort led by the [https://public.nrao.edu/ National Radio Astronomy Observatory]. The current version of CASA uses Python (2.7) interface. More information about CASA can be found on [https://casa.nrao.edu/ NRAO's CASA website ]. Note, CASA is available ONLY on UNIX-BASED PLATFORMS (and therefore, so is SunCASA).
** [https://github.com/Gelu-Nita/GSFIT GSFIT] A IDL-widget(GUI)-based spectral fitting package called gsfit, which provides a user-friendly display of EOVSA image cubes and an interface to fast fitting codes (via platform-dependent shared-object libraries).
** [https://github.com/suncasa/pygsfit pyGSFIT] A Python-widget(pyQT)-based spectral fitting package, which provides a user-friendly display of EOVSA image cubes, spatially resolved spectra, and an interface to scipy-based fitting codes.
** [[Spectrogram Software]]
** [[Mapping Software]]
* <big>Data Analysis Guides (for those who start from raw data) </big>






**[[Tohban Guide to Self Calibration and Imaging for EOVSA]] Step-to-step guide for manually making images from raw visibility data.
**[[EOVSA flare pipeline]] Description of the EOVSA flare pipeline and tutorial for running it to produce quicklook images.



* <big>EOVSA Modeling Guide</big>
**[[GX Simulator]]

* Other helpful links
** [https://casaguides.nrao.edu CASA Guides]
** [http://www.lmsal.com/solarsoft/ SolarSoft IDL]
** [http://www.atnf.csiro.au/computing/software/miriad/userguide/userhtml.html Miriad Guides]
** [https://sites.google.com/site/fgscodes/ Fast Gyrosynchrotron Codes (Alexey Kuznetsov's website)]
** [[Basic GitHub Tutorial]]


* <big>[[Full Disk Simulations]]</big>
* <big>[[All-Day Synthesis Issues]]</big>
* <big>[[Analyzing Pre-2017 Data]]</big>
* <big>[[Fixing Pipeline Problems pre-2021-Feb-07]]</big>

== EOVSA Documentation ==

* <big>General</big>
** [[Downconversion and Frequency Tuning]]
** [[Dealing with Radio Frequency Interference]]
** [[Switching between 200 MHz and 300 MHz Correlator]]
** [[Observing in "Fast" Mode]]

* <big>Computer-Network</big>
** [[Computing Systems]]
** [[Network]]

* <big>Control System</big>
** [[27-m Antenna Commands]]
** [[Schedule Commands]]
** [[Control Commands]]
** [[Attenuation and Level Control]]

* <big>Hardware</big>
** [[Hardware Overview]]
** [[2.1-m Antennas]]
** [[27-m Antennas]]

* <big>System Software</big>
** [[Calibration Database]]
** [[Stateframe Database]]
** [[Database Maintenance]]
** [[Create CASA measurement sets]]

* <big>Calibration</big>
**[[Calibration Overview]]
**[[Pointing Calibration]]
**[[Total Power Calibration]]
**[[System Gain Calibration]]
**[[Antenna Position]] (Baseline Calibration)
**[[Reference Gain Calibration]]
**[[Daily Gain Calibration]]
**[[Delay Calibration]]
**[[Bandpass Calibration]]
**[[Polarization Calibration]]
**[[Calibrator Survey]]
**[[Practical Calibration Tutorial]]

* <big>[[Starburst]]</big>

== EOVSA System Software ==

* LabVIEW software
* Python code [https://github.com/dgary50/eovsa Github repository]
* [[Python3 Code Installation]]

== Using OVRO-LWA data ==

* <big>[[OVRO-LWA Data Products]]</big>: An introduction to standard OVRO-LWA spectrogram and spectral image products with example scripts for reading and plotting.
* <big>[[OVRO-LWA Data Policy]]</big>: Policy for using OVRO-LWA data products.

== EOVSA Observing Log ==
[[2016 November]]; [[2016 December| December]]

[[2017 January]]; [[2017 February | February]]; [[2017 March | March]]; [[2017 April | April]]; [[2017 May | May]]; [[2017 June | June]];
[[2017 July | July]]; [[2017 August | August]]; [[2017 September | September]]; [[2017 October | October]]; [[2017 November | November]]; [[2017 December | December]]

[[2018 January]]; [[2018 February | February]]; [[2018 March | March]]; [[2018 April | April]]; [[2018 May | May]]; [[2018 June | June]];
[[2018 July | July]]; [[2018 August | August]]; [[2018 September | September]]; [[2018 October | October]]; [[2018 November | November]]; [[2018 December | December]]

[[2019 January]]; [[2019 February | February]]; [[2019 March | March]]; [[2019 April | April]]; [[2019 May | May]]; [[2019 June | June]];
[[2019 July | July]]; [[2019 August | August]]; [[2019 September | September]]; [[2019 October | October]]; [[2019 November | November]]; [[2019 December | December]]

[[2020 January]]; [[2020 February | February]]; [[2020 March | March]]; [[2020 April | April]]; [[2020 May | May]]; [[2020 June | June]];
[[2020 July | July]]; [[2020 August | August]]; [[2020 September | September]]; [[2020 October | October]]; [[2020 November | November]]; [[2020 December | December]]

[[2021 January]]; [[2021 February | February]]; [[2021 March | March]]; [[2021 April | April]]; [[2021 May | May]]; [[2021 June | June]];
[[2021 July | July]]; [[2021 August | August]]; [[2021 September | September]]; [[2021 October | October]]; [[2021 November | November]]; [[2021 December | December]]

[[2022 SQL Outage]]

[[2023 January]]; [[2023 February | February]]; [[2023 March | March]]; [[2023 April | April]]; [[2023 May | May]]; [[2023 June | June]];
[[2023 July | July]]; [[2023 August | August]]; [[2023 September | September]]; [[2023 October | October]]; [[2023 November | November]]; [[2023 December | December]]

[[2024 January]]; [[2024 February | February]]; [[2024 March | March]]; [[2024 April | April]]; [[2024 May |May]]; [[2024 June | June]]; [[2024 July | July]]; [[2024 August | August]];
[[2024 September | September]]; [[2024 October | October]]; [[2024 November | November]]; [[2024 December | December]]

[[2025 January]]; [[2025 February | February]]; [[2025 March | March]]; [[2025 April | April]]; [[2025 May |May]]; [[2025 June | June]]; [[2025 July | July]]; [[2025 August | August]];
[[2025 September | September]]; [[2025 October | October]]; [[2025 November | November]]; [[2025 December | December]]

== OVSA Scientist on Duty ==
* Scientist on Duty (SoD): OVSA team members take turns and serve as a SoD to work with our onsite observatory staff on day-to-day observing. They are also responsible for monitoring solar activities and ensuring that the data we collect is of high quality.
* SoD observing logs ([https://drive.google.com/drive/folders/1q6-0Z9B0CPFutuTqzmeheEUSJM3tEL2o?usp=drive_link directory to all logs]):
** 2024: [https://docs.google.com/document/d/1QDWw5y4HpcE7CSpzXwftMqQT4FDgNJj-6fRrgWrqdug/edit?usp=sharing May (and before that)], [https://docs.google.com/document/d/1Rh2gYBV2E454xVYEv8jx5IXKd1N2Z05ns4dhI2XCE08/edit?usp=sharing June], [https://docs.google.com/document/d/1beUpp6rgwjqSxKbuHzXIR9hhPrGyi0j-SjtEIeav9Vg/edit?usp=sharing July], [https://docs.google.com/document/d/1pSzUXW5gd-4cZAR-gglTUVM_J2UHMa4wYJ2AzD4cdEo/edit?usp=sharing August], [https://docs.google.com/document/d/18pArAP0kRDhXHbty_y3TtrygmWkC2oLn-UD7njIpRIo/edit?usp=sharing September], [https://docs.google.com/document/d/1Qt6vhrqPAOG7W5Y_tLiod_QgNR1FDyzRxQcg6_oJQd4/edit?usp=sharing October], [https://docs.google.com/document/d/1pv9-Wne80FCrg0J5BkjOafmof_s3jlnc9HwyzWkIBfU/edit?usp=sharing November], [https://docs.google.com/document/d/1O5svOVwQZbUON1GMR_8nBR5LAL0M8RM2_zWW4oeBiLk/edit?usp=sharing December]
** 2025: [https://docs.google.com/document/d/1pUdSRyWgQa2py1PSLa3CKs_DDqL_SOgx6MMIp4cPnpk/edit?usp=sharing January],[https://docs.google.com/document/d/18cnIAaeM8UBiYPtsQn7g6TM8mjr57blSoY9l-6ShhwQ/edit?usp=sharing February], [https://docs.google.com/document/d/1k60i7nabWltnU38I7fGS2uq2-FUe5TMAKcM1BeLIRdY/edit?usp=sharing March], [https://docs.google.com/document/d/1CMaXBtA1ULNFbzuawYirP913A6dTa68cbYk2a7knirI/edit?usp=sharing April], [https://docs.google.com/document/d/13Kr8lYfFN9bzgFvCJi6nBUxbQHa3_eTgfjwaCUn3vCs/edit?tab=t.0 May], [https://docs.google.com/document/d/1ptGvQiB6SPgzJ-I6IgJ4bKK-3GPK-4LBpq7BG6sFPSg/edit?usp=sharing June], [https://docs.google.com/document/d/1XrOonOdwrkSDSWT2CwvzIaw7aRxBA4Sba1GCMRmkDZk/edit?usp=sharing July], [https://docs.google.com/document/d/1MzKkL8cPaBLNDOuws4U0ATuTN7kVaaeX4dUp0cga3vo/edit?usp=sharing August], [https://docs.google.com/document/d/14JHnHLZiDTqtK_cmaHgRevKksHuqijBQcMo1zcrz98k/edit?usp=sharing September]
* SoD instructions:
** Daily routines: see [https://docs.google.com/document/d/1_iGnMRRrvb85Z0vT8-LzgQmCOKDSATEuQ0vTsn2C-dc/edit?usp=sharing SoD Routines] for detailed instructions.
** Instructions for [[making quick-look flare spectrograms and movies]]

==OVRO-LWA Solar-Dedicated Spectroscopic Imager==
The OVRO-LWA (Owens Valley Radio Observatory Long Wavelength Array) has recently been upgraded to include a solar-dedicated beam and two solar imaging modes (slow visibilities of 352 antennas with a 10-s cadence, and fast visibilities of 48 antennas with a 0.1-s cadence). The large collecting area and excellent calibration provide unprecedented high-sensitivity imaging of the quiet Sun and bursts. The array is currently in commissioning and observations are not yet continuous, but they are becoming more so. See the daily realtime data at http://ovsa.njit.edu/status.php for '''real-time display of the spectrogram and a selection of images''', both updated on a 1-min cadence.

===Solar-Dedicated Modes===
* Beamformer: The OVRO-LWA beamformer uses the 256 antennas in the core region to form a synthesized beam of more than 1 degree in size that tracks the Sun from sunrise to sunset. This permits a continuous record of the full-Stokes total flux (without spatial resolution) of the Sun (a dynamic spectrum) with 24 kHz frequency resolution (3072 frequencies from 13.4-86.9 MHz) and as low as 1 ms time resolution.

* Standard Interferometric Imaging (also known as "Slow Visibilities"): In this mode, the entire 352-element array is interferometrically correlated to provide visibilities for imaging at all 3072 frequencies at 10-s time resolution. This is ideal for imaging quiet Sun and slowly-varying emission such as coronal mass ejections and active region variability.

* Bursty Interferometric Imaging (also known as "Fast Visibilities"): In this mode, a subset of 48 antennas (chosen to include mainly outer antennas to maintain good spatial resolution) is interferometrically correlated to provide visibilities for imaging at 768 frequencies (96 kHz frequency resolution) at 0.1-s time resolution. This is ideal for imaging rapidly varying emission such as type II and type III bursts as well as many other solar spectral fine structures.

===Data Access===
* OVRO-LWA solar data release v1.0 is available! Please refer to the [[OVRO-LWA Data Products]] page for more information.

===OVRO-LWA Operation Notes===

[[OVRO-LWA Operation Notes]]

== Tohbans ==

[[Trouble Shooting Guide]]

[[Tohban Records]]

[[Owen's Notes]]

[[Caius' Notes]]

[[Tohban EOVSA Imaging Tutorial A-Z]]

[[Tohban OVRO-LWA Imaging Tutorial]]

[[Tohban Guide to Self Calibration and Imaging for EOVSA]]

[[Guide to Upgrade SolarSoft(SSW)]]

[[Star Pointing Notes]]

== VLA Flare List and Publications ==
See [http://www.ovsa.njit.edu/wiki/index.php/VLA_Data_Survey#List_of_Jansky_VLA_Solar_Observations this link] for a list of flare observations made by the [https://science.nrao.edu/facilities/vla/ Karl G. Jansky Very Large Array] (VLA). Below is a partial list of publications that utilize VLA solar data (see also [https://ui.adsabs.harvard.edu/public-libraries/ZwbjpLo9RS-viufWEoQ95Q this NASA/ADS Library]).
* [https://ui.adsabs.harvard.edu/abs/2022ApJ...940..137L/abstract Luo et al. (2022), ApJ, 940, 137] ''Multiple Regions of Nonthermal Quasiperiodic Pulsations during the Impulsive Phase of a Solar Flare''
* [https://ui.adsabs.harvard.edu/abs/2021ApJ...922..134B/abstract Battaglia et al. (2021), ApJ, 922, 134] ''Multiple Electron Acceleration Instances during a Series of Solar Microflares Observed Simultaneously at X-Rays and Microwaves''
* [https://ui.adsabs.harvard.edu/abs/2021ApJ...911....4L/abstract Luo et al. (2021), ApJ, 911, 4] ''Radio Spectral Imaging of an M8.4 Eruptive Solar Flare: Possible Evidence of a Termination Shock''
* [https://ui.adsabs.harvard.edu/abs/2021ApJ...910...40Z/abstract Zhang et al. (2021), ApJ, 910, 40] ''Multiwavelength Observations of the Formation and Eruption of a Complex Filament''
* [https://ui.adsabs.harvard.edu/abs/2020ApJ...904...94S/abstract Sharma et al. (2020), ApJ, 904, 94] ''Radio and X-Ray Observations of Short-lived Episodes of Electron Acceleration in a Solar Microflare''
* [https://ui.adsabs.harvard.edu/abs/2019ApJ...884...63C/abstract Chen et al. (2019), ApJ, 884, 63] ''Radio Spectroscopic Imaging of a Solar Flare Termination Shock: Split-band Feature as Evidence for Shock Compression''
* [https://ui.adsabs.harvard.edu/abs/2019ApJ...872...71Y/abstract Yu & Chen (2019), ApJ, 872, 71] ''Possible Detection of Subsecond-period Propagating Magnetohydrodynamics Waves in Post-reconnection Magnetic Loops during a Two-ribbon Solar Flare''
* [https://ui.adsabs.harvard.edu/abs/2018ApJ...866...62C/abstract Chen et al. (2018), ApJ, 866, 62] ''Magnetic Reconnection Null Points as the Origin of Semirelativistic Electron Beams in a Solar Jet
''
* [https://ui.adsabs.harvard.edu/abs/2017ApJ...848...77W/abstract Wang et al. (2016), ApJ, 848, 77] ''Dynamic Spectral Imaging of Decimetric Fiber Bursts in an Eruptive Solar Flare''
* [https://ui.adsabs.harvard.edu/abs/2015Sci...350.1238C/abstract Chen et al. (2015), Science, 350, 1238] ''Particle acceleration by a solar flare termination shock''
* [https://ui.adsabs.harvard.edu/abs/2014ApJ...794..149C/abstract Chen et al. (2014), ApJ, 794, 149] ''Direct Evidence of an Eruptive, Filament-hosting Magnetic Flux Rope Leading to a Fast Solar Coronal Mass Ejection''
* [https://ui.adsabs.harvard.edu/abs/2013ApJ...763L..21C/abstract Chen et al. (2013), ApJL, 763, 21] ''Tracing Electron Beams in the Sun's Corona with Radio Dynamic Imaging Spectroscopy''

==Radio Data from Around The Heliosphere==
* [http://ovsa.njit.edu//wiki/index.php/Radio_Data_from_Around_the_World#Radio_Data_Access '' Radio Data '']

==Radio Astronomy Lecture Notes==
Here is a link to the [[Radio Astronomy Lecture Notes]] adapted from the Phys728: Radio Astronomy graduate-level course Prof. Dale Gary taught at NJIT until Spring 2019.

OVRO-LWA Solar Data Products

2025-09-11T17:40:59Z

Binchen: /* Data Release Versions and Change Log */

=Introduction=
OVRO-LWA is an all-sky radio imager by design and hence, in principle, can observe the Sun as long as it is above the horizon. However, the array is located in a valley surrounded by mountains, and hence the Sun is not visible from the array when its line-of-sight from the array passes through the mountains. Additionally, when the Sun is at very low elevations, the performance of the array degrades, and the data gets increasingly affected by terrestrial radio emission. Keeping this in mind, the Sun is observed with the OVRO-LWA when the solar elevation is greater than approximately 15 degrees. This translates to about 7-14 hours of observations depending on the season.

The highest time-frequency resolution at which data can be obtained with the OVRO-LWA in a regular manner is 1 ms and 24 kHz, respectively. However, depending on the observation mode as well as due to data rate limitations, the actual available time-frequency resolution can vary. The figure and table below summarize the different data products we produce. The later sections will give a more detailed description and usage examples.
[[File:OVRO-LWA_data_product_flowchart.png|center|800px|OVRO-LWA data product flowchart]]

{| class="wikitable"
|+ Summary of OVSA-LWA Data Release v1.0
|-
! scope="col"| Observation Type
! scope="col"| Data Product
! scope="col"| Description
! scope="col"| Naming Convention
! scope="col"| Format
! scope="col"| Data Rate (GB/day)
|-
! rowspan="2" | Beamforming Spectrograms
| All-day Total-Power Spectrograms: Level 1.0
| Stokes I, 13.4-86.9 MHz in 768 channels, 256-ms cadence, 96-kHz spectral resolution; complex gain and flux calibrated
| ovro-lwa.lev1_bmf_256ms_96kHz.YYYY-MM-DD.dspec_I.fits
| FITS
| 0.6 GB/day
|-
| All-day Total-Power Spectrograms: Level 1.5
| Same as level 1.0, but with additional subtraction of non-Sun background and primary beam corrections
| ovro-lwa.lev1.5_bmf_256ms_96kHz.YYYY-MM-DD.dspec_I.fits
| FITS
| 0.6 GB/day
|-
! rowspan="4" | Standard Interferometric Spectral Images
| Fine-Channel Spectral Images: Level 1.0
| Stokes I, 32-87 MHz in 144 channels, 10-s integration, 20-60-s cadence, 384 kHz resolution; complex gain, bandpass, and flux calibrated
| ovro-lwa-352.lev1_fch_10s.YYYY-MM-DDTHHMMSSZ.image_I.hdf
| HDF
| 45 GB/day
|-
| Fine-Channel Spectral Images: Level 1.5
| Same as level 1.0, but with additional refraction correction during quiet times when the solar disk is seen
| ovro-lwa-352.lev1.5_fch_10s.YYYY-MM-DDTHHMMSSZ.image_I.hdf
| HDF
| ~20-40 GB/day
|-
| Band-Averaged Spectral Images: Level 1.0
| Stokes I, 32-87 MHz in 12 channels, 10-s integration, 20-60-s cadence, 4.6 MHz resolution; complex gain, bandpass, and flux calibrated
| ovro-lwa-352.lev1_mfs_10s.YYYY-MM-DDTHHMMSSZ.image_I.hdf
| HDF
| 4 GB/day
|-
| Band-Averaged Spectral Images: Level 1.5
| Same as level 1.0, but with additional refraction correction during quiet times when the solar disk is seen
| ovro-lwa-352.lev1.5_mfs_10s.YYYY-MM-DDTHHMMSSZ.image_I.hdf
| HDF
| ~2-4 GB/day
|-
|}

=Level 0 - Raw Data=

OVRO-LWA, in general, operates multiple observing modes simultaneously. This is achieved by passing the raw data stream from the 352 antennas through multiple data handling processes, with each process handling an observation mode. The figure above summarizes the three data streams relevant to the solar data. These data streams are:
* '''Beamforming Dynamic Spectroscopy Data''': The OVRO-LWA beamformer uses the 256 antennas in the core region to form a synthesized beam of more than 1 degree in size that tracks the Sun from sunrise to sunset. This permits a continuous record of the full-Stokes total flux (without spatial resolution) of the Sun (a dynamic spectrum) with 24 kHz frequency resolution (3072 frequency channels from 13.4-86.9 MHz) and as low as 1 ms time resolution. For regular solar observations, we write data out with full spectral resolution and 64 ms time resolution. These raw data are permanently stored in the Hierarchical Data Format (HDF) on our data server. The level-0 spectrograms are generated in true real-time (with <1-s of latency). Quicklook spectrograms, in PNG format, are displayed on our [https://ovsa.njit.edu/status.php# observing status page]. Note that the level-0 spectrograms are already partially calibrated. They have close-to-true flux scale, but they contain the non-solar background and have not been corrected for the primary beam response.
* '''Standard Interferometric Imaging''' (also known as "slow visibilities"): In this mode, the entire 352-element array is interferometrically correlated to provide visibilities for imaging at all 3072 frequencies at 10-s time resolution. This mode is ideal for high-dynamic-range, high-fidelity imaging of relatively slowly varying emissions, such as active regions, coronal holes, and incoherent emission from coronal mass ejections. The data is stored in CASA's measurement set format (see [https://casadocs.readthedocs.io/en/stable/notebooks/casa-fundamentals.html this link] for more details). With a daily data rate of 17 TB, we currently do not have the capacity to store all the raw data. Hence, they are stored in a 7-day rolling "buffer." Extremely interesting/important events will be copied and saved on a case-by-case basis. Our automatic pipeline processes the data into spectral images at a reduced cadence and spectral resolution (see next section).
* '''Bursty Interferometric Imaging''' (also known as "fast visibilities"): In this mode, a subset of 48 antennas (chosen to include mainly outer antennas to maintain good spatial resolution) is interferometrically correlated to provide visibilities for imaging at 768 frequencies (96 kHz frequency resolution) at 0.1-s time resolution. This mode is ideal for imaging rapidly varying emission with fine spectro-temporal structures, such as type II and type III bursts with spectral fine structures. The trade-off is the imaging dynamic range and fidelity. The data is also stored in CASA's measurement set format. With a daily data rate of 9 TB, we currently do not have the capacity to store all the raw data. Hence, they are stored in a 3-day rolling "buffer." Extremely interesting/important events will be copied and saved on a case-by-case basis. A pipeline for processing the data into spectral images in a "triggered" mode is currently under construction.

=Level 1.0 - Calibrated Spectrogram and Spectral Imaging Data=

As mentioned in the previous section, the level-0 raw spectrograms are already partially calibrated. The level-1 total-power spectrograms convert the raw data in HDF format into the standard FITS format in Stokes I, with all necessary information stored in the header. No additional calibrations/corrections are made during this process. Please refer to the next section for more discussions on additional calibrations/corrections to advance them to level 1.5.

The level-0 raw standard interferometric imaging data are processed with appropriate calibrations (complex gain, bandpass, and absolute flux scale), performing self-calibration, and finally, synthesis imaging to convert them into level 1.0 spectral images. A pipeline for processing polarized data products is being constructed and tested. The standard interferometric images are generated in near real-time (with several minutes of latency). Quicklook images and movies at selected frequency bands, in PNG format, are displayed on our [https://ovsa.njit.edu/status.php# observing status page]. The spectral image data themselves are stored and provided in HDF format. We also provide software to convert the HDF5 files to FITS file format. The produced FITS files, apart from the multi-frequency data, also contain a table containing the frequencies corresponding to the multi-frequency images and the instrumental resolution at each frequency. It also contains other parameters necessary to convert the images to level 1.5, which might be useful for some scientific purposes. These images are in heliocentric coordinates and typically have a dynamic range of >300 (the dynamic range of an image refers to the ratio of the image maximum and the image "noise," usually represented by rms of a source-free region). The FITS images can be directly loaded into Python or SSWIDL using standard techniques.

Although OVRO-LWA obtains fully polarized data, for the current data release (v1.0), we provide Stokes I data products only. We are preparing a paper on the pipeline, which will provide more details of the data processing steps above.

Here are descriptions for each of these level 1 data products.

* '''Level-1 Total-Power Spectrograms''': The total-power spectrogram data are provided as standard FITS tables containing the frequency list, list of times, and the Stokes I flux density in SFU. The data are averaged to 256 ms time resolution and 96 kHz frequency resolution (i.e., a binning factor of 4 for both time and frequency).

* '''Level-1 Standard Fine-Channel Spectral Images''': Each file, in HDF format, contains independent images made at 144 frequency channels equally spaced between 32 and 87 MHz. Each image has a frequency integrating factor of 16, resulting in an effective spectral resolution of 384 kHz. Each image has an integration time of 10s. The cadence varies between ~60s in early 2024 to ~20s in 2025, and in some cases, full 10-s cadence for selected events.

* '''Level-1 Standard Band-Averaged Spectral Images''': The file format is the same as the fine-channel spectral images. The calibrated visibility data are further combined using multi-frequency-synthesis imaging, resulting in 12 images with center frequencies of 34.1, 38.7, 43.2, 47.8, 52.4, 57.0, 61.6, 66.2, 70.8, 75.4, 80.0, and 84.6 MHz. Each image has a frequency integrating factor of 192, resulting in an effective spectral resolution of 4.6 MHz. The time integration and cadence are the same as the fine-channel spectral images.

=Level 1.5 - Further Processed Spectrograms and Images=

Level 1.5 spectrograms and images have all calibrations for the level 1 products, but with additional corrections, which are briefly described below.

* '''Level 1.5 Beamforming Spectrograms''': Two corrections are performed at this stage: background subtraction and primary beam correction. The primary necessity of performing both these corrections stems from the fact that each of the OVRO-LWA cross-dipole antennas has a response to the entire sky (from horizon to horizon). Hence, all sources present in the sky contribute non-zero flux density to the observed dynamic spectrum. To determine the solar flux density, the contribution of the background sky (all sources in the sky except Sun) is estimated and subtracted from the observed dynamic spectrum. Additionally, the OVRO-LWA dipoles have a non-uniform response across the sky. For example, the effective "gain" of the beamforming mode to the Sun at high altitudes is greater than that at lower altitudes. This also needs to be corrected to determine the true solar flux density and its evolution with time and frequency. The primary beam correction parameters are based on the current primary beam model, and are time- and frequency-dependent. The exact primary beam model used for the corrections is stored in the FITS header.
* '''Level 1.5 Standard Spectral Images''': When propagating through the Earth's ionosphere, low-frequency radio waves are affected by various ionospheric effects. The most profound is the frequency-dependent source shifts due to refraction, which are inversely proportional to the square of the observation frequency. For the Level 1.5 spectral images, we attempt to correct for such refraction effects using this dependence. However, this ionospheric-refraction-induced source shift could be mixed with frequency-dependent source variations intrinsic to the emitter. When there are no strong bursts on the Sun, we can use the quiet Sun disk itself as the reference to correct for the ionospheric refraction effects. This is done by comparing the observed centroids (using the "center of mass" of burst-free regions of the Sun) of the solar disk with the expected center of the Sun to derive the frequency-dependent source shifts. The derived shifts are then fitted to the expected 1/frequency^2 law and applied to the images at all frequencies. However, this method is not applicable when there are strong bursts on the Sun across multiple frequency channels. Hence, the level 1.5 spectral image products are not always available, esp. during periods of strong solar activity. We also note that such corrections are still experimental. Please use the data products with care.

=Reading and Plotting OVRO-LWA Data Products=

===OVRO-LWA Level 1/1.5 Spectrograms===
*For '''Python users''': An example of how to read and plot the OVRO-LWA level 1/1.5 spectrograms can be accessed at [https://colab.research.google.com/drive/16rIcxitcPaNS06pP5UmGOjsucpE5SZii?usp=drive_link this Google Colab Jupyter notebook]. The required packages are Astropy, Numpy, and Matplotlib.
*For '''SSWIDL users''': We will provide a minimal example to read and plot the data with SSWIDL. Please stay tuned.

===OVRO-LWA Level 1/1.5 Spectral Images===
*For '''Python users''': An example of how to read and plot the OVRO-LWA level 1/1.5 spectral images can be accessed at [https://colab.research.google.com/drive/1h76sg5P8H5Xy0VGsvpEWcSfhSs5tZBfm?usp=sharing this Google Colab Jupyter notebook]. The required packages are Astropy, SunPy, H5py, SciPy, Numpy, and Matplotlib.
*For '''SSWIDL users''': We will provide a minimal example to read and plot the data with SSWIDL. Please stay tuned.

=Data Release Versions and Change Log=
{| class="wikitable"
|+ Summary of OVRO-LWA Solar Data Release Versions
|-
! scope="col"| Version #
! scope="col"| Release Date
! scope="col"| Affected Data Period
! scope="col"| Link to documentation
|-
| v1.0
| 2025/09/01
| 2024/01/01 - present
| Current page
|-
|}

OVSA Science Highlight No. 4: When the Sun Meets the Crab

2025-09-11T15:38:13Z

Binchen:

''Contributed by '''Peijin Zhang'''<sup>1, 2</sup> (<sup>1</sup>Center for Solar-Terrestrial Research, New Jersey Institute of Technology, 323 Martin Luther King Jr Blvd., Newark, NJ 07102-1982, USA; <sup>2</sup> Cooperative Programs for the Advancement of Earth System Science, University Corporation for Atmospheric Research, Boulder, CO, USA''); Edited by B. Chen.

Being situated in the Zodiac constellation Taurus, the [https://en.wikipedia.org/wiki/Crab_Nebula Crab Nebula] (also known as Tau A), is in conjunction with the Sun in mid-June every year. During the conjunction, the crab is completely outshone by the Sun in optical wavelengths. However, at meter-decameter wavelengths, the Sun is no longer dazzlingly bright anymore; the radio brightness of the Crab Nebula can be up to one-tenth that of the quiet Sun! Thus, the two can be observed together with a radio telescope that has a sufficiently large field of view and a dynamic range that is adequate for imaging both of them.

During such conjunctions, the radio image of the Crab Nebula is broadened and distorted by the heliospheric plasma as the radio waves propagate through it. The broadening/distortion effect is more profound as the Crab Nebula gets closer to the Sun. These observations, in turn, provide us with a unique opportunity to study the turbulent structures in the extended solar corona, which is otherwise challenging to measure remotely.

This effect was predicted not long after the birth of radio astronomy. In Figure 1, Hewish (1958) showed his prediction of what the Crab Nebula would look like as it approaches the Sun (Figure 1).

{| class="wikitable" style="border: none;"
|-
| style="width:800px;" | [[File:PZhang2025_fig1.jpg|800px]]
|-
| style="width:800px;" | Figure 1: Left: isotropic‑scattering prediction for a compact background source near the Sun (Hewish 1958). Right: 2024 OVRO‑LWA observation of the Crab during conjunction showing arc‑like broadening and substructure.
|}

We observed the Crab Nebula (Tau A) during its 2024 solar conjunction with the [https://ovsa.njit.edu/ Owens Valley Radio Observatory’s Long Wavelength Array (OVRO‑LWA)], imaging 30–80 MHz at projected heliocentric distances of ≈5–27 R⊙. OVRO-LWA has both a large field of view and high image dynamic range – the right combination for studying conjunctions. These observations produced daily, wide‑field images that quantify how scattering varies with frequency and impact parameter, sampling three key dates near closest approach (e.g., Jun 9, Jun 14, and Jun 22). Figure 2 shows such multi-frequency "time-lapse" images of the Crab Nebula's 2024 solar conjunction as observed by OVRO-LWA.

{| class="wikitable" style="border: none;"
|-
| style="width:800px;" | [[File:PZhang2025_fig2.jpg|800px]]
|-
| style="width:800px;" | Figure 2: OVRO-LWA's multi-frequency time-lapse of the Crab Nebula during its solar conjunction from June 9, 2024, to June 22, 2024.
|}

With the angular broadening measurement, we found that the anisotropic ratio decreases along the radial direction. Also, near the closest approach, the image became arc‑like and showed substructure at the lowest frequencies, especially when the line of sight crossed dense coronal streamers (features that align with contemporaneous white‑light streamer structure), which we interpret as evidence for the presence of mesoscale density inhomogeneities. In addition, the observed total flux decreased toward lower frequency and smaller impact parameter, consistent with stronger scattering/absorption in denser plasma.

These measurements quantify how magnetic‑field‑guided turbulence varies with heliocentric distance and how it tangentially broadens background sources (affecting apparent position and flux). They offer important and unique diagnostic value to inform radio‑wave propagation models and improve the interpretation of heliospheric radio observations.

----

''Based on the recent paper by Zhang, P., Mondal, S., Chen, B., Yu, S., Gary, D. et al. (2025), "Probing the Turbulent Corona and Heliosphere Using Radio Spectral Imaging Observation during the Solar Conjunction of Crab Nebula," The Astrophysical Journal, in press. [https://arxiv.org/abs/2506.01632 Arxiv: 2506.01632]''

== References ==

* [https://ui.adsabs.harvard.edu/abs/1958MNRAS.118..534H/abstract Hewish, A. "The scattering of radio waves in the solar corona." Monthly Notices of the Royal Astronomical Society 118.6 (1958): 534-546.]

OVRO-LWA Solar Data Products

2025-08-25T16:40:55Z

Binchen: /* Level 1.5 - Images */

=Introduction=
OVRO-LWA is an all-sky radio imager by design and hence, in principle, can observe the Sun as long as it is above the horizon. However, the array is located in a valley surrounded by mountains, and hence the Sun is not visible from the array when its line-of-sight from the array passes through the mountains. Additionally, when the Sun is at very low elevations, the performance of the array degrades, and the data gets increasingly affected by terrestrial radio emission. Keeping this in mind, the Sun is observed with the OVRO-LWA when the solar elevation is greater than approximately 15 degrees. This translates to about 7-14 hours of observations depending on the season.

The highest time-frequency resolution at which data can be obtained with the OVRO-LWA in a regular manner is 1 ms and 24 kHz, respectively. However, depending on the observation mode as well as due to data rate limitations, the actual available time-frequency resolution can vary. The figure and table below summarize the different data products we produce. The later sections will give a more detailed description and usage examples.
[[File:OVRO-LWA_data_product_flowchart.png|center|800px|OVRO-LWA data product flowchart]]

{| class="wikitable"
|+ Summary of OVSA-LWA Data Products for Release v1.0
|-
! scope="col"| Observation Type
! scope="col"| Data Product
! scope="col"| Description
! scope="col"| Naming Convention
! scope="col"| Format
! scope="col"| Data Rate (GB/day)
|-
! rowspan="2" | Beamforming Spectrograms
| All-day Total-Power Spectrograms: Level 1.0
| Stokes I, 13.4-86.9 MHz in 768 channels, 256-ms cadence, 96-kHz spectral resolution; complex gain and flux calibrated
| ovro-lwa.lev1_bmf_256ms_96kHz.YYYY-MM-DD.dspec_I.fits
| FITS
| 0.6 GB/day
|-
| All-day Total-Power Spectrograms: Level 1.5
| Same as level 1.0, but with additional subtraction of non-Sun background and primary beam corrections
| ovro-lwa.lev1.5_bmf_256ms_96kHz.YYYY-MM-DD.dspec_I.fits
| FITS
| 0.6 GB/day
|-
! rowspan="4" | Standard Interferometric Spectral Images
| Fine-Channel Spectral Images: Level 1.0
| Stokes I, 32-87 MHz in 144 channels, 10-s integration, 20-60-s cadence, 384 kHz resolution; complex gain, bandpass, and flux calibrated
| ovro-lwa-352.lev1_fch_10s.YYYY-MM-DDTHHMMSSZ.image_I.hdf
| HDF
| 45 GB/day
|-
| Fine-Channel Spectral Images: Level 1.5
| Same as level 1.0, but with additional refraction correction during quiet times when the solar disk is seen
| ovro-lwa-352.lev1.5_fch_10s.YYYY-MM-DDTHHMMSSZ.image_I.hdf
| HDF
| ~20-40 GB/day
|-
| Band-Averaged Spectral Images: Level 1.0
| Stokes I, 32-87 MHz in 12 channels, 10-s integration, 20-60-s cadence, 4.6 MHz resolution; complex gain, bandpass, and flux calibrated
| ovro-lwa-352.lev1_mfs_10s.YYYY-MM-DDTHHMMSSZ.image_I.hdf
| HDF
| 4 GB/day
|-
| Band-Averaged Spectral Images: Level 1.5
| Same as level 1.0, but with additional refraction correction during quiet times when the solar disk is seen
| ovro-lwa-352.lev1.5_mfs_10s.YYYY-MM-DDTHHMMSSZ.image_I.hdf
| HDF
| ~2-4 GB/day
|-
|}

=Level 0 - Raw Data=

OVRO-LWA, in general, operates multiple observing modes simultaneously. This is achieved by passing the raw data stream from the 352 antennas through multiple data handling processes, with each process handling an observation mode. The figure above summarizes the three data streams relevant to the solar data. These data streams are:
* '''Beamforming Dynamic Spectroscopy Data''': The OVRO-LWA beamformer uses the 256 antennas in the core region to form a synthesized beam of more than 1 degree in size that tracks the Sun from sunrise to sunset. This permits a continuous record of the full-Stokes total flux (without spatial resolution) of the Sun (a dynamic spectrum) with 24 kHz frequency resolution (3072 frequency channels from 13.4-86.9 MHz) and as low as 1 ms time resolution. For regular solar observations, we write data out with full spectral resolution and 64 ms time resolution. These raw data are permanently stored in the Hierarchical Data Format (HDF) on our data server. The level-0 spectrograms are generated in true real-time (with <1-s of latency). Quicklook spectrograms, in PNG format, are displayed on our [https://ovsa.njit.edu/status.php# observing status page]. Note that the level-0 spectrograms are already partially calibrated. They have close-to-true flux scale, but they contain the non-solar background and have not been corrected for the primary beam response.
* '''Standard Interferometric Imaging''' (also known as "slow visibilities"): In this mode, the entire 352-element array is interferometrically correlated to provide visibilities for imaging at all 3072 frequencies at 10-s time resolution. This mode is ideal for high-dynamic-range, high-fidelity imaging of relatively slowly varying emissions, such as active regions, coronal holes, and incoherent emission from coronal mass ejections. The data is stored in CASA's measurement set format (see [https://casadocs.readthedocs.io/en/stable/notebooks/casa-fundamentals.html this link] for more details). With a daily data rate of 17 TB, we currently do not have the capacity to store all the raw data. Hence, they are stored in a 7-day rolling "buffer." Extremely interesting/important events will be copied and saved on a case-by-case basis. Our automatic pipeline processes the data into spectral images at a reduced cadence and spectral resolution (see next section).
* '''Bursty Interferometric Imaging''' (also known as "fast visibilities"): In this mode, a subset of 48 antennas (chosen to include mainly outer antennas to maintain good spatial resolution) is interferometrically correlated to provide visibilities for imaging at 768 frequencies (96 kHz frequency resolution) at 0.1-s time resolution. This mode is ideal for imaging rapidly varying emission with fine spectro-temporal structures, such as type II and type III bursts with spectral fine structures. The trade-off is the imaging dynamic range and fidelity. The data is also stored in CASA's measurement set format. With a daily data rate of 9 TB, we currently do not have the capacity to store all the raw data. Hence, they are stored in a 3-day rolling "buffer." Extremely interesting/important events will be copied and saved on a case-by-case basis. A pipeline for processing the data into spectral images in a "triggered" mode is currently under construction.

=Level 1.0 - Calibrated Spectrogram and Spectral Imaging Data=

As mentioned in the previous section, the level-0 raw spectrograms are already partially calibrated. The level-1 total-power spectrograms convert the raw data in HDF format into the standard FITS format in Stokes I, with all necessary information stored in the header. No additional calibrations/corrections are made during this process.

The level-0 raw standard interferometric imaging data are processed with appropriate calibrations (complex gain, bandpass, and absolute flux scale), performing self-calibration, and finally, synthesis imaging to convert them into spectral images. A pipeline for processing polarized data products is being constructed and tested. The standard interferometric images are generated in near real-time (with several minutes of latency). Quicklook images and movies at selected frequency bands, in PNG format, are displayed on our [https://ovsa.njit.edu/status.php# observing status page]. The spectral image data themselves are stored and provided in HDF format. We also provide software to convert the HDF5 files to FITS file format. The produced FITS files, apart from the multi-frequency data, also contain a table containing the frequencies corresponding to the multi-frequency images and the instrumental resolution at each frequency. It also contains other parameters necessary to convert the images to level 1.5, which might be useful for some scientific purposes. These images are in heliocentric coordinates and typically have a dynamic range of >300 (the dynamic range of an image refers to the ratio of the image maximum and the image "noise," usually represented by rms of a source-free region). The FITS images can be directly loaded into Python or SSWIDL using standard techniques.

Although OVRO-LWA obtains fully polarized data, for the current data release (v1.0), we provide Stokes I data products only. We are preparing a paper on the pipeline, which will provide more details of the data processing steps above.

Here are descriptions for each of these level 1 data products.

* '''Level-1 Total-Power Spectrograms''': The total-power spectrogram data are provided as standard FITS tables containing the frequency list, list of times, and the Stokes I flux density in SFU. The data are averaged to 256 ms time resolution and 96 kHz frequency resolution (i.e., a binning factor of 4 for both time and frequency).

* '''Level-1 Standard Fine-Channel Spectral Images''': Each file, in HDF format, contains independent images made at 144 frequency channels equally spaced between 32 and 87 MHz. Each image has a frequency integrating factor of 16, resulting in an effective spectral resolution of 384 kHz. Each image has an integration time of 10s. The cadence varies between ~60s in early 2024 to ~20s in 2025, and in some cases, full 10-s cadence for selected events.

* '''Level-1 Standard Band-Averaged Spectral Images''': The file format is the same as the fine-channel spectral images. The calibrated visibility data are further combined using multi-frequency-synthesis imaging, resulting in 12 images with center frequencies of 34, 39, 43, 48, 52, 57, 62, 66, 71, 75, 80, and 84 MHz. Each image has a frequency integrating factor of 192, resulting in an effective spectral resolution of 4.6 MHz. The time integration and cadence are the same as the fine-channel spectral images.

=Level 1.5 - Further Processed Spectrograms and Images=

''Something about the level 1.5 spectrograms.''

Low radio frequency waves, during propagation, get significantly affected by ionospheric refraction. Ionospheric refraction often results in source shifts only, without any change of the source morphology and flux density. In this case, it can be shown that the source shift is inversely proportional to the square of the observation frequency. Here this dependence is used to try to correct for refraction. The proportionality constant is directly dependent on the gradient of the ionospheric total electron count along the line-of-sight towards the source. When the sun is quiet, the imaging dynamic range is sufficiently high to easily see the quiet sun disc. Hence the ionospheric source shift can be determined by comparing the observed center of the solar disc with the optical location of the Sun. The source shifts at multiple frequencies can be fitted to obtain the ionospheric parameters, and then can be applied to the images at other frequencies, where the solar disc is not well observed due to dynamic range limitations.

OVRO-LWA Solar Data Products

2025-08-20T15:05:55Z

Binchen: /* Introduction */

Owens Valley Solar Arrays

2025-08-20T12:58:45Z

Binchen: /* Latest OVSA Science Highlights */

[[File:Eovsa1.png|border|text-top|800px]]

<big>[http://ovsa.njit.edu/ EOVSA] (Expanded Owens Valley Solar Array) is a solar-dedicated radio interferometer operated by the New Jersey Institute of Technology and serving as a '''National Science Foundation Geospace Facility'''. [[File:NSF.jpg|70px]]
<pre>Operation of EOVSA is supported by the National Science Foundation under Grant No. AGS-2130832. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. </pre>
This wiki serves as the site for EOVSA documentation. </big>

[[File:OVRO-LWA1.png|border|text-top|800px]]

<big>OVRO-LWA (Owens Valley Radio Observatory Long Wavelength Array) is an all-sky imager that has a new solar-dedicated spectroscopic imaging mode. OVRO-LWA is a multi-institutional collaboration led by Caltech. NJIT Solar Radio Group is leading its solar-mode development and science. At the bottom of this page are new links for that facility. </big>

== Latest OVSA Science Highlights ==

[[OVSA Science Highlight No. 3: The First EOVSA "Cold" Solar Flare]]
[[File:cold_flare.jpeg|left|100px]]
This study takes advantage of EOVSA's microwave imaging spectroscopy capability and multi-wavelength observations to measure the coronal magnetic field and track the flare energy partitioning. The results show ample magnetic free energy to drive efficient electron acceleration, with the energy deposition of nonthermal electrons alone accounting for the observed thermal response, reinforcing cold flares as clean cases of particle-driven heating. [Contributed by Gregory Fleishman (New Jersey Institute of Technology); Edited by B. Chen. Posted on August 20, 2025.]

<div style="clear: both;"></div>

[[OVSA Science Highlight No. 2: Two Phases of Impulsive SEP Acceleration]]
[[File:SEP_illustration_gemini.jpeg|left|100px]]
[https://iopscience.iop.org/article/10.3847/1538-4357/adbdd0 M. Wang et al.] analyze a solar energetic particle (SEP) event associated with an eruptive X-class flare and found two distinct impulsive SEP acceleration phases. They are suggested to link to different magnetic reconnection regimes during the eruption, which govern the timing and energy of particles released into interplanetary space. [Contributed by Meiqi Wang (New Jersey Institute of Technology); Edited by B. Chen. Posted on August 19, 2025.]

<div style="clear: both;"></div>

[[OVSA Science Highlight No. 1: Microwave Precursor of a Major Solar Eruption]]
[[File:solar_eruption_nasa.jpeg|left|100px]]
A study by [https://iopscience.iop.org/article/10.3847/2041-8213/adf063 Y. Kou et al.] presents the first spatially resolved microwave imaging spectroscopy of the precursor phase of a major solar eruption. The findings reveal that thermal electron emissions dominate during the slow-rise phase, supporting a scenario of moderate magnetic reconnection prior to the flare’s impulsive onset. [Contributed by Yuankun Kou (Nanjing University); Edited by B. Chen. Posted on August 2, 2025.]

<div style="clear: both;"></div>

We welcome contributions at all times. Please refer to the [[OVSA Science Highlights]] page for guidelines and a complete list of highlights.

<div style="clear: both;"></div>

== OVSA Publications ==
Our collection of publications that utilize OVSA data is available at [https://ui.adsabs.harvard.edu/public-libraries/eQ7HfPkySqydu-B8BCt6QQ this NASA/ADS Library]. If you have a paper that is missing from this library, please email Bin Chen (bin.chen [at] njit.edu).


== EOVSA Flare List ==

* [https://ovsa.njit.edu/flarelist Query EOVSA Flare list]
* List of EOVSA flares in separate years: [[2025]], [[2024]], [[2023]], [[2022]], [[2021]], [[2020]], [[2019]], [[2017]]

== Using OVSA Data ==
* <big>[[EOVSA Data Products]]</big>: An introduction to standard EOVSA spectrogram and spectral image products with example scripts for reading and plotting.
* <big>[[EOVSA Data Policy]]</big>: Policy for using EOVSA data products.
* <big>Analysis Software</big>: These are for in-depth use of EOVSA data (from calibrated visibilities) and tools for quantitative analysis.
** [https://github.com/suncasa/suncasa SunCASA] A wrapper around [https://casa.nrao.edu/ CASA (the Common Astronomy Software Applications package)] for synthesis imaging and visualizing solar spectral imaging data. CASA is one of the leading software tool for "supporting the data post-processing needs of the next generation of radio astronomical telescopes such as ALMA and VLA", an international effort led by the [https://public.nrao.edu/ National Radio Astronomy Observatory]. The current version of CASA uses Python (2.7) interface. More information about CASA can be found on [https://casa.nrao.edu/ NRAO's CASA website ]. Note, CASA is available ONLY on UNIX-BASED PLATFORMS (and therefore, so is SunCASA).
** [https://github.com/Gelu-Nita/GSFIT GSFIT] A IDL-widget(GUI)-based spectral fitting package called gsfit, which provides a user-friendly display of EOVSA image cubes and an interface to fast fitting codes (via platform-dependent shared-object libraries).
** [https://github.com/suncasa/pygsfit pyGSFIT] A Python-widget(pyQT)-based spectral fitting package, which provides a user-friendly display of EOVSA image cubes, spatially resolved spectra, and an interface to scipy-based fitting codes.
** [[Spectrogram Software]]
** [[Mapping Software]]
* <big>Data Analysis Guides (for those who start from raw data) </big>






**[[Tohban Guide to Self Calibration and Imaging for EOVSA]] Step-to-step guide for manually making images from raw visibility data.
**[[EOVSA flare pipeline]] Description of the EOVSA flare pipeline and tutorial for running it to produce quicklook images.



* <big>EOVSA Modeling Guide</big>
**[[GX Simulator]]

* Other helpful links
** [https://casaguides.nrao.edu CASA Guides]
** [http://www.lmsal.com/solarsoft/ SolarSoft IDL]
** [http://www.atnf.csiro.au/computing/software/miriad/userguide/userhtml.html Miriad Guides]
** [https://sites.google.com/site/fgscodes/ Fast Gyrosynchrotron Codes (Alexey Kuznetsov's website)]
** [[Basic GitHub Tutorial]]


* <big>[[Full Disk Simulations]]</big>
* <big>[[All-Day Synthesis Issues]]</big>
* <big>[[Analyzing Pre-2017 Data]]</big>
* <big>[[Fixing Pipeline Problems pre-2021-Feb-07]]</big>

== EOVSA Documentation ==

* <big>General</big>
** [[Downconversion and Frequency Tuning]]
** [[Dealing with Radio Frequency Interference]]
** [[Switching between 200 MHz and 300 MHz Correlator]]
** [[Observing in "Fast" Mode]]

* <big>Computer-Network</big>
** [[Computing Systems]]
** [[Network]]

* <big>Control System</big>
** [[27-m Antenna Commands]]
** [[Schedule Commands]]
** [[Control Commands]]
** [[Attenuation and Level Control]]

* <big>Hardware</big>
** [[Hardware Overview]]
** [[2.1-m Antennas]]
** [[27-m Antennas]]

* <big>System Software</big>
** [[Calibration Database]]
** [[Stateframe Database]]
** [[Database Maintenance]]
** [[Create CASA measurement sets]]

* <big>Calibration</big>
**[[Calibration Overview]]
**[[Pointing Calibration]]
**[[Total Power Calibration]]
**[[System Gain Calibration]]
**[[Antenna Position]] (Baseline Calibration)
**[[Reference Gain Calibration]]
**[[Daily Gain Calibration]]
**[[Delay Calibration]]
**[[Bandpass Calibration]]
**[[Polarization Calibration]]
**[[Calibrator Survey]]
**[[Practical Calibration Tutorial]]

* <big>[[Starburst]]</big>

== EOVSA System Software ==

* LabVIEW software
* Python code [https://github.com/dgary50/eovsa Github repository]
* [[Python3 Code Installation]]

== Using OVRO-LWA data ==

* <big>[[OVRO-LWA Data Products]]</big>: An introduction to standard OVRO-LWA spectrogram and spectral image products with example scripts for reading and plotting.
* <big>[[OVRO-LWA Data Policy]]</big>: Policy for using OVRO-LWA data products.

== EOVSA Observing Log ==
[[2016 November]]; [[2016 December| December]]

[[2017 January]]; [[2017 February | February]]; [[2017 March | March]]; [[2017 April | April]]; [[2017 May | May]]; [[2017 June | June]];
[[2017 July | July]]; [[2017 August | August]]; [[2017 September | September]]; [[2017 October | October]]; [[2017 November | November]]; [[2017 December | December]]

[[2018 January]]; [[2018 February | February]]; [[2018 March | March]]; [[2018 April | April]]; [[2018 May | May]]; [[2018 June | June]];
[[2018 July | July]]; [[2018 August | August]]; [[2018 September | September]]; [[2018 October | October]]; [[2018 November | November]]; [[2018 December | December]]

[[2019 January]]; [[2019 February | February]]; [[2019 March | March]]; [[2019 April | April]]; [[2019 May | May]]; [[2019 June | June]];
[[2019 July | July]]; [[2019 August | August]]; [[2019 September | September]]; [[2019 October | October]]; [[2019 November | November]]; [[2019 December | December]]

[[2020 January]]; [[2020 February | February]]; [[2020 March | March]]; [[2020 April | April]]; [[2020 May | May]]; [[2020 June | June]];
[[2020 July | July]]; [[2020 August | August]]; [[2020 September | September]]; [[2020 October | October]]; [[2020 November | November]]; [[2020 December | December]]

[[2021 January]]; [[2021 February | February]]; [[2021 March | March]]; [[2021 April | April]]; [[2021 May | May]]; [[2021 June | June]];
[[2021 July | July]]; [[2021 August | August]]; [[2021 September | September]]; [[2021 October | October]]; [[2021 November | November]]; [[2021 December | December]]

[[2022 SQL Outage]]

[[2023 January]]; [[2023 February | February]]; [[2023 March | March]]; [[2023 April | April]]; [[2023 May | May]]; [[2023 June | June]];
[[2023 July | July]]; [[2023 August | August]]; [[2023 September | September]]; [[2023 October | October]]; [[2023 November | November]]; [[2023 December | December]]

[[2024 January]]; [[2024 February | February]]; [[2024 March | March]]; [[2024 April | April]]; [[2024 May |May]]; [[2024 June | June]]; [[2024 July | July]]; [[2024 August | August]];
[[2024 September | September]]; [[2024 October | October]]; [[2024 November | November]]; [[2024 December | December]]

[[2025 January]]; [[2025 February | February]]; [[2025 March | March]]; [[2025 April | April]]; [[2025 May |May]]; [[2025 June | June]]; [[2025 July | July]]; [[2025 August | August]];
[[2025 September | September]]; [[2025 October | October]]; [[2025 November | November]]; [[2025 December | December]]

== OVSA Scientist on Duty ==
* Scientist on Duty (SoD): OVSA team members take turns and serve as a SoD to work with our onsite observatory staff on day-to-day observing. They are also responsible for monitoring solar activities and ensuring that the data we collect is of high quality.
* SoD observing logs ([https://drive.google.com/drive/folders/1q6-0Z9B0CPFutuTqzmeheEUSJM3tEL2o?usp=drive_link directory to all logs]):
** 2024: [https://docs.google.com/document/d/1QDWw5y4HpcE7CSpzXwftMqQT4FDgNJj-6fRrgWrqdug/edit?usp=sharing May (and before that)], [https://docs.google.com/document/d/1Rh2gYBV2E454xVYEv8jx5IXKd1N2Z05ns4dhI2XCE08/edit?usp=sharing June], [https://docs.google.com/document/d/1beUpp6rgwjqSxKbuHzXIR9hhPrGyi0j-SjtEIeav9Vg/edit?usp=sharing July], [https://docs.google.com/document/d/1pSzUXW5gd-4cZAR-gglTUVM_J2UHMa4wYJ2AzD4cdEo/edit?usp=sharing August], [https://docs.google.com/document/d/18pArAP0kRDhXHbty_y3TtrygmWkC2oLn-UD7njIpRIo/edit?usp=sharing September], [https://docs.google.com/document/d/1Qt6vhrqPAOG7W5Y_tLiod_QgNR1FDyzRxQcg6_oJQd4/edit?usp=sharing October], [https://docs.google.com/document/d/1pv9-Wne80FCrg0J5BkjOafmof_s3jlnc9HwyzWkIBfU/edit?usp=sharing November], [https://docs.google.com/document/d/1O5svOVwQZbUON1GMR_8nBR5LAL0M8RM2_zWW4oeBiLk/edit?usp=sharing December]
** 2025: [https://docs.google.com/document/d/1pUdSRyWgQa2py1PSLa3CKs_DDqL_SOgx6MMIp4cPnpk/edit?usp=sharing January],[https://docs.google.com/document/d/18cnIAaeM8UBiYPtsQn7g6TM8mjr57blSoY9l-6ShhwQ/edit?usp=sharing February], [https://docs.google.com/document/d/1k60i7nabWltnU38I7fGS2uq2-FUe5TMAKcM1BeLIRdY/edit?usp=sharing March], [https://docs.google.com/document/d/1CMaXBtA1ULNFbzuawYirP913A6dTa68cbYk2a7knirI/edit?usp=sharing April], [https://docs.google.com/document/d/13Kr8lYfFN9bzgFvCJi6nBUxbQHa3_eTgfjwaCUn3vCs/edit?tab=t.0 May], [https://docs.google.com/document/d/1ptGvQiB6SPgzJ-I6IgJ4bKK-3GPK-4LBpq7BG6sFPSg/edit?usp=sharing June], [https://docs.google.com/document/d/1XrOonOdwrkSDSWT2CwvzIaw7aRxBA4Sba1GCMRmkDZk/edit?usp=sharing July], [https://docs.google.com/document/d/1MzKkL8cPaBLNDOuws4U0ATuTN7kVaaeX4dUp0cga3vo/edit?usp=sharing August]
* SoD instructions:
** Daily routines: see [https://docs.google.com/document/d/1_iGnMRRrvb85Z0vT8-LzgQmCOKDSATEuQ0vTsn2C-dc/edit?usp=sharing SoD Routines] for detailed instructions.
** Instructions for [[making quick-look flare spectrograms and movies]]

==OVRO-LWA Solar-Dedicated Spectroscopic Imager==
The OVRO-LWA (Owens Valley Radio Observatory Long Wavelength Array) has recently been upgraded to include a solar-dedicated beam and two solar imaging modes (slow visibilities of 352 antennas with a 10-s cadence, and fast visibilities of 48 antennas with a 0.1-s cadence). The large collecting area and excellent calibration provide unprecedented high-sensitivity imaging of the quiet Sun and bursts. The array is currently in commissioning and observations are not yet continuous, but they are becoming more so. See the daily realtime data at http://ovsa.njit.edu/status.php for '''real-time display of the spectrogram and a selection of images''', both updated on a 1-min cadence.

===Solar-Dedicated Modes===
* Beamformer: the beamformer uses the 256 core antennas to form a synthesized beam of more than 1 degree in size that tracks the Sun from sunrise to sunset. This permits a continuous record of the full-Stokes total flux (without spatial resolution) of the Sun (a dynamic spectrum) with 24 kHz frequency resolution (3072 frequencies from 15-90 MHz) and as low as 1 ms time resolution.

* Slow Visibility Imaging: in this mode, the entire 352-element array is interferometrically correlated to provide visibilities for imaging at all 3072 frequencies at 10-s time resolution. This is ideal for imaging quiet Sun and slowly-varying emission such as coronal mass ejections and active region variability.

* Fast Visibility Imaging: in this mode, a subset of 48 antennas (chosen to include mainly outer antennas to maintain good spatial resolution) is interferometrically correlated to provide visibilities for imaging at 768 frequencies (96 kHz frequency resolution) at 0.1-s time resolution. This is ideal for imaging rapidly varying emission such as type II and type III bursts as well as many other solar spectral fine structures.

===Inital Data Access===
In its current commissioning state, we try to run the beamformer and imaging pipeline every day in real-time since November 2023 (no latency for beamforming spectrograms and 5-10 min latency for images). Quicklook real-time spectrograms/images can be accessed from http://ovsa.njit.edu/status.php. To access data from previous days, use the following links (replace yyyymmdd with the date you desire):
* Quicklook beamformer total-power spectrograms: http://ovsa.njit.edu/lwa-data/1min_spectra/yyyymmdd/. Check this link for additional daily plots [[Daily OVRO-LWA Beamformer Data]].
* Quicklook multi-frequency movies at 1-min cadence: http://ovsa.njit.edu/lwa-data/1min_images/yyyymmdd/movie_yyyy-mm-dd.html

Note our pipeline processing development is still in the early phase. For example, absolute flux calibrations have not been done for the beamformer spectrograms. Also, artificial effects (including ionospheric refraction effects) are present in the images that cause distortions/shifts. We caution interested users only to consider them for quick-look purposes at this point. Please contact the EOVSA PIs (Dale Gary, Bin Chen) if you intend to use them for science.

===OVRO-LWA Operation Notes===

[[OVRO-LWA Operation Notes]]

== Tohbans ==

[[Trouble Shooting Guide]]

[[Tohban Records]]

[[Owen's Notes]]

[[Caius' Notes]]

[[Tohban EOVSA Imaging Tutorial A-Z]]

[[Tohban OVRO-LWA Imaging Tutorial]]

[[Tohban Guide to Self Calibration and Imaging for EOVSA]]

[[Guide to Upgrade SolarSoft(SSW)]]

[[Star Pointing Notes]]

== VLA Flare List and Publications ==
See [http://www.ovsa.njit.edu/wiki/index.php/VLA_Data_Survey#List_of_Jansky_VLA_Solar_Observations this link] for a list of flare observations made by the [https://science.nrao.edu/facilities/vla/ Karl G. Jansky Very Large Array] (VLA). Below is a partial list of publications that utilize VLA solar data (see also [https://ui.adsabs.harvard.edu/public-libraries/ZwbjpLo9RS-viufWEoQ95Q this NASA/ADS Library]).
* [https://ui.adsabs.harvard.edu/abs/2022ApJ...940..137L/abstract Luo et al. (2022), ApJ, 940, 137] ''Multiple Regions of Nonthermal Quasiperiodic Pulsations during the Impulsive Phase of a Solar Flare''
* [https://ui.adsabs.harvard.edu/abs/2021ApJ...922..134B/abstract Battaglia et al. (2021), ApJ, 922, 134] ''Multiple Electron Acceleration Instances during a Series of Solar Microflares Observed Simultaneously at X-Rays and Microwaves''
* [https://ui.adsabs.harvard.edu/abs/2021ApJ...911....4L/abstract Luo et al. (2021), ApJ, 911, 4] ''Radio Spectral Imaging of an M8.4 Eruptive Solar Flare: Possible Evidence of a Termination Shock''
* [https://ui.adsabs.harvard.edu/abs/2021ApJ...910...40Z/abstract Zhang et al. (2021), ApJ, 910, 40] ''Multiwavelength Observations of the Formation and Eruption of a Complex Filament''
* [https://ui.adsabs.harvard.edu/abs/2020ApJ...904...94S/abstract Sharma et al. (2020), ApJ, 904, 94] ''Radio and X-Ray Observations of Short-lived Episodes of Electron Acceleration in a Solar Microflare''
* [https://ui.adsabs.harvard.edu/abs/2019ApJ...884...63C/abstract Chen et al. (2019), ApJ, 884, 63] ''Radio Spectroscopic Imaging of a Solar Flare Termination Shock: Split-band Feature as Evidence for Shock Compression''
* [https://ui.adsabs.harvard.edu/abs/2019ApJ...872...71Y/abstract Yu & Chen (2019), ApJ, 872, 71] ''Possible Detection of Subsecond-period Propagating Magnetohydrodynamics Waves in Post-reconnection Magnetic Loops during a Two-ribbon Solar Flare''
* [https://ui.adsabs.harvard.edu/abs/2018ApJ...866...62C/abstract Chen et al. (2018), ApJ, 866, 62] ''Magnetic Reconnection Null Points as the Origin of Semirelativistic Electron Beams in a Solar Jet
''
* [https://ui.adsabs.harvard.edu/abs/2017ApJ...848...77W/abstract Wang et al. (2016), ApJ, 848, 77] ''Dynamic Spectral Imaging of Decimetric Fiber Bursts in an Eruptive Solar Flare''
* [https://ui.adsabs.harvard.edu/abs/2015Sci...350.1238C/abstract Chen et al. (2015), Science, 350, 1238] ''Particle acceleration by a solar flare termination shock''
* [https://ui.adsabs.harvard.edu/abs/2014ApJ...794..149C/abstract Chen et al. (2014), ApJ, 794, 149] ''Direct Evidence of an Eruptive, Filament-hosting Magnetic Flux Rope Leading to a Fast Solar Coronal Mass Ejection''
* [https://ui.adsabs.harvard.edu/abs/2013ApJ...763L..21C/abstract Chen et al. (2013), ApJL, 763, 21] ''Tracing Electron Beams in the Sun's Corona with Radio Dynamic Imaging Spectroscopy''

==Radio Data from Around The Heliosphere==
* [http://ovsa.njit.edu//wiki/index.php/Radio_Data_from_Around_the_World#Radio_Data_Access '' Radio Data '']

==Radio Astronomy Lecture Notes==
Here is a link to the [[Radio Astronomy Lecture Notes]] adapted from the Phys728: Radio Astronomy graduate-level course Prof. Dale Gary taught at NJIT until Spring 2019.

Owens Valley Solar Arrays

2025-08-19T14:02:10Z

Binchen: /* Latest OVSA Science Highlights */

[[File:Eovsa1.png|border|text-top|800px]]

<big>[http://ovsa.njit.edu/ EOVSA] (Expanded Owens Valley Solar Array) is a solar-dedicated radio interferometer operated by the New Jersey Institute of Technology and serving as a '''National Science Foundation Geospace Facility'''. [[File:NSF.jpg|70px]]
<pre>Operation of EOVSA is supported by the National Science Foundation under Grant No. AGS-2130832. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. </pre>
This wiki serves as the site for EOVSA documentation. </big>

[[File:OVRO-LWA1.png|border|text-top|800px]]

<big>OVRO-LWA (Owens Valley Radio Observatory Long Wavelength Array) is an all-sky imager that has a new solar-dedicated spectroscopic imaging mode. OVRO-LWA is a multi-institutional collaboration led by Caltech. NJIT Solar Radio Group is leading its solar-mode development and science. At the bottom of this page are new links for that facility. </big>

== Latest OVSA Science Highlights ==

[[OVSA Science Highlight No. 2: Two Phases of Impulsive SEP Acceleration]]
[[File:solar_eruption_nasa.jpeg|left|100px]]
[https://iopscience.iop.org/article/10.3847/1538-4357/adbdd0 M. Wang et al.] analyze a solar energetic particle (SEP) event associated with an eruptive X-class flare and found two distinct impulsive SEP acceleration phases. They are suggested to link to different magnetic reconnection regimes during the eruption, which govern the timing and energy of particles released into interplanetary space. [Contributed by Meiqi Wang (New Jersey Institute of Technology); Edited by B. Chen. Posted on August 19, 2025.]

<div style="clear: both;"></div>

[[OVSA Science Highlight No. 1: Microwave Precursor of a Major Solar Eruption]]
[[File:solar_eruption_nasa.jpeg|left|100px]]
A study by [https://iopscience.iop.org/article/10.3847/2041-8213/adf063 Y. Kou et al.] presents the first spatially resolved microwave imaging spectroscopy of the precursor phase of a major solar eruption. The findings reveal that thermal electron emissions dominate during the slow-rise phase, supporting a scenario of moderate magnetic reconnection prior to the flare’s impulsive onset. [Contributed by Yuankun Kou (Nanjing University); Edited by B. Chen. Posted on August 2, 2025.]

<div style="clear: both;"></div>

We welcome contributions at all times. Please refer to the [[OVSA Science Highlights]] page for guidelines and a complete list of highlights.

<div style="clear: both;"></div>

== OVSA Publications ==
Our collection of publications that utilize OVSA data is available at [https://ui.adsabs.harvard.edu/public-libraries/eQ7HfPkySqydu-B8BCt6QQ this NASA/ADS Library]. If you have a paper that is missing from this library, please email Bin Chen (bin.chen [at] njit.edu).


== EOVSA Flare List ==

* [https://ovsa.njit.edu/flarelist Query EOVSA Flare list]
* List of EOVSA flares in separate years: [[2025]], [[2024]], [[2023]], [[2022]], [[2021]], [[2020]], [[2019]], [[2017]]

== Using OVSA Data ==
* <big>[[EOVSA Data Products]]</big>: An introduction to standard EOVSA spectrogram and spectral image products with example scripts for reading and plotting.
* <big>[[EOVSA Data Policy]]</big>: Policy for using EOVSA data products.
* <big>Analysis Software</big>: These are for in-depth use of EOVSA data (from calibrated visibilities) and tools for quantitative analysis.
** [https://github.com/suncasa/suncasa SunCASA] A wrapper around [https://casa.nrao.edu/ CASA (the Common Astronomy Software Applications package)] for synthesis imaging and visualizing solar spectral imaging data. CASA is one of the leading software tool for "supporting the data post-processing needs of the next generation of radio astronomical telescopes such as ALMA and VLA", an international effort led by the [https://public.nrao.edu/ National Radio Astronomy Observatory]. The current version of CASA uses Python (2.7) interface. More information about CASA can be found on [https://casa.nrao.edu/ NRAO's CASA website ]. Note, CASA is available ONLY on UNIX-BASED PLATFORMS (and therefore, so is SunCASA).
** [https://github.com/Gelu-Nita/GSFIT GSFIT] A IDL-widget(GUI)-based spectral fitting package called gsfit, which provides a user-friendly display of EOVSA image cubes and an interface to fast fitting codes (via platform-dependent shared-object libraries).
** [https://github.com/suncasa/pygsfit pyGSFIT] A Python-widget(pyQT)-based spectral fitting package, which provides a user-friendly display of EOVSA image cubes, spatially resolved spectra, and an interface to scipy-based fitting codes.
** [[Spectrogram Software]]
** [[Mapping Software]]
* <big>Data Analysis Guides (for those who start from raw data) </big>






**[[Tohban Guide to Self Calibration and Imaging for EOVSA]] Step-to-step guide for manually making images from raw visibility data.
**[[EOVSA flare pipeline]] Description of the EOVSA flare pipeline and tutorial for running it to produce quicklook images.



* <big>EOVSA Modeling Guide</big>
**[[GX Simulator]]

* Other helpful links
** [https://casaguides.nrao.edu CASA Guides]
** [http://www.lmsal.com/solarsoft/ SolarSoft IDL]
** [http://www.atnf.csiro.au/computing/software/miriad/userguide/userhtml.html Miriad Guides]
** [https://sites.google.com/site/fgscodes/ Fast Gyrosynchrotron Codes (Alexey Kuznetsov's website)]
** [[Basic GitHub Tutorial]]


* <big>[[Full Disk Simulations]]</big>
* <big>[[All-Day Synthesis Issues]]</big>
* <big>[[Analyzing Pre-2017 Data]]</big>
* <big>[[Fixing Pipeline Problems pre-2021-Feb-07]]</big>

== EOVSA Documentation ==

* <big>General</big>
** [[Downconversion and Frequency Tuning]]
** [[Dealing with Radio Frequency Interference]]
** [[Switching between 200 MHz and 300 MHz Correlator]]
** [[Observing in "Fast" Mode]]

* <big>Computer-Network</big>
** [[Computing Systems]]
** [[Network]]

* <big>Control System</big>
** [[27-m Antenna Commands]]
** [[Schedule Commands]]
** [[Control Commands]]
** [[Attenuation and Level Control]]

* <big>Hardware</big>
** [[Hardware Overview]]
** [[2.1-m Antennas]]
** [[27-m Antennas]]

* <big>System Software</big>
** [[Calibration Database]]
** [[Stateframe Database]]
** [[Database Maintenance]]
** [[Create CASA measurement sets]]

* <big>Calibration</big>
**[[Calibration Overview]]
**[[Pointing Calibration]]
**[[Total Power Calibration]]
**[[System Gain Calibration]]
**[[Antenna Position]] (Baseline Calibration)
**[[Reference Gain Calibration]]
**[[Daily Gain Calibration]]
**[[Delay Calibration]]
**[[Bandpass Calibration]]
**[[Polarization Calibration]]
**[[Calibrator Survey]]
**[[Practical Calibration Tutorial]]

* <big>[[Starburst]]</big>

== EOVSA System Software ==

* LabVIEW software
* Python code [https://github.com/dgary50/eovsa Github repository]
* [[Python3 Code Installation]]

== Using OVRO-LWA data ==

* <big>[[OVRO-LWA Data Products]]</big>: An introduction to standard OVRO-LWA spectrogram and spectral image products with example scripts for reading and plotting.
* <big>[[OVRO-LWA Data Policy]]</big>: Policy for using OVRO-LWA data products.

== EOVSA Observing Log ==
[[2016 November]]; [[2016 December| December]]

[[2017 January]]; [[2017 February | February]]; [[2017 March | March]]; [[2017 April | April]]; [[2017 May | May]]; [[2017 June | June]];
[[2017 July | July]]; [[2017 August | August]]; [[2017 September | September]]; [[2017 October | October]]; [[2017 November | November]]; [[2017 December | December]]

[[2018 January]]; [[2018 February | February]]; [[2018 March | March]]; [[2018 April | April]]; [[2018 May | May]]; [[2018 June | June]];
[[2018 July | July]]; [[2018 August | August]]; [[2018 September | September]]; [[2018 October | October]]; [[2018 November | November]]; [[2018 December | December]]

[[2019 January]]; [[2019 February | February]]; [[2019 March | March]]; [[2019 April | April]]; [[2019 May | May]]; [[2019 June | June]];
[[2019 July | July]]; [[2019 August | August]]; [[2019 September | September]]; [[2019 October | October]]; [[2019 November | November]]; [[2019 December | December]]

[[2020 January]]; [[2020 February | February]]; [[2020 March | March]]; [[2020 April | April]]; [[2020 May | May]]; [[2020 June | June]];
[[2020 July | July]]; [[2020 August | August]]; [[2020 September | September]]; [[2020 October | October]]; [[2020 November | November]]; [[2020 December | December]]

[[2021 January]]; [[2021 February | February]]; [[2021 March | March]]; [[2021 April | April]]; [[2021 May | May]]; [[2021 June | June]];
[[2021 July | July]]; [[2021 August | August]]; [[2021 September | September]]; [[2021 October | October]]; [[2021 November | November]]; [[2021 December | December]]

[[2022 SQL Outage]]

[[2023 January]]; [[2023 February | February]]; [[2023 March | March]]; [[2023 April | April]]; [[2023 May | May]]; [[2023 June | June]];
[[2023 July | July]]; [[2023 August | August]]; [[2023 September | September]]; [[2023 October | October]]; [[2023 November | November]]; [[2023 December | December]]

[[2024 January]]; [[2024 February | February]]; [[2024 March | March]]; [[2024 April | April]]; [[2024 May |May]]; [[2024 June | June]]; [[2024 July | July]]; [[2024 August | August]];
[[2024 September | September]]; [[2024 October | October]]; [[2024 November | November]]; [[2024 December | December]]

[[2025 January]]; [[2025 February | February]]; [[2025 March | March]]; [[2025 April | April]]; [[2025 May |May]]; [[2025 June | June]]; [[2025 July | July]]; [[2025 August | August]];
[[2025 September | September]]; [[2025 October | October]]; [[2025 November | November]]; [[2025 December | December]]

== OVSA Scientist on Duty ==
* Scientist on Duty (SoD): OVSA team members take turns and serve as a SoD to work with our onsite observatory staff on day-to-day observing. They are also responsible for monitoring solar activities and ensuring that the data we collect is of high quality.
* SoD observing logs ([https://drive.google.com/drive/folders/1q6-0Z9B0CPFutuTqzmeheEUSJM3tEL2o?usp=drive_link directory to all logs]):
** 2024: [https://docs.google.com/document/d/1QDWw5y4HpcE7CSpzXwftMqQT4FDgNJj-6fRrgWrqdug/edit?usp=sharing May (and before that)], [https://docs.google.com/document/d/1Rh2gYBV2E454xVYEv8jx5IXKd1N2Z05ns4dhI2XCE08/edit?usp=sharing June], [https://docs.google.com/document/d/1beUpp6rgwjqSxKbuHzXIR9hhPrGyi0j-SjtEIeav9Vg/edit?usp=sharing July], [https://docs.google.com/document/d/1pSzUXW5gd-4cZAR-gglTUVM_J2UHMa4wYJ2AzD4cdEo/edit?usp=sharing August], [https://docs.google.com/document/d/18pArAP0kRDhXHbty_y3TtrygmWkC2oLn-UD7njIpRIo/edit?usp=sharing September], [https://docs.google.com/document/d/1Qt6vhrqPAOG7W5Y_tLiod_QgNR1FDyzRxQcg6_oJQd4/edit?usp=sharing October], [https://docs.google.com/document/d/1pv9-Wne80FCrg0J5BkjOafmof_s3jlnc9HwyzWkIBfU/edit?usp=sharing November], [https://docs.google.com/document/d/1O5svOVwQZbUON1GMR_8nBR5LAL0M8RM2_zWW4oeBiLk/edit?usp=sharing December]
** 2025: [https://docs.google.com/document/d/1pUdSRyWgQa2py1PSLa3CKs_DDqL_SOgx6MMIp4cPnpk/edit?usp=sharing January],[https://docs.google.com/document/d/18cnIAaeM8UBiYPtsQn7g6TM8mjr57blSoY9l-6ShhwQ/edit?usp=sharing February], [https://docs.google.com/document/d/1k60i7nabWltnU38I7fGS2uq2-FUe5TMAKcM1BeLIRdY/edit?usp=sharing March], [https://docs.google.com/document/d/1CMaXBtA1ULNFbzuawYirP913A6dTa68cbYk2a7knirI/edit?usp=sharing April], [https://docs.google.com/document/d/13Kr8lYfFN9bzgFvCJi6nBUxbQHa3_eTgfjwaCUn3vCs/edit?tab=t.0 May], [https://docs.google.com/document/d/1ptGvQiB6SPgzJ-I6IgJ4bKK-3GPK-4LBpq7BG6sFPSg/edit?usp=sharing June], [https://docs.google.com/document/d/1XrOonOdwrkSDSWT2CwvzIaw7aRxBA4Sba1GCMRmkDZk/edit?usp=sharing July], [https://docs.google.com/document/d/1MzKkL8cPaBLNDOuws4U0ATuTN7kVaaeX4dUp0cga3vo/edit?usp=sharing August]
* SoD instructions:
** Daily routines: see [https://docs.google.com/document/d/1_iGnMRRrvb85Z0vT8-LzgQmCOKDSATEuQ0vTsn2C-dc/edit?usp=sharing SoD Routines] for detailed instructions.
** Instructions for [[making quick-look flare spectrograms and movies]]

==OVRO-LWA Solar-Dedicated Spectroscopic Imager==
The OVRO-LWA (Owens Valley Radio Observatory Long Wavelength Array) has recently been upgraded to include a solar-dedicated beam and two solar imaging modes (slow visibilities of 352 antennas with a 10-s cadence, and fast visibilities of 48 antennas with a 0.1-s cadence). The large collecting area and excellent calibration provide unprecedented high-sensitivity imaging of the quiet Sun and bursts. The array is currently in commissioning and observations are not yet continuous, but they are becoming more so. See the daily realtime data at http://ovsa.njit.edu/status.php for '''real-time display of the spectrogram and a selection of images''', both updated on a 1-min cadence.

===Solar-Dedicated Modes===
* Beamformer: the beamformer uses the 256 core antennas to form a synthesized beam of more than 1 degree in size that tracks the Sun from sunrise to sunset. This permits a continuous record of the full-Stokes total flux (without spatial resolution) of the Sun (a dynamic spectrum) with 24 kHz frequency resolution (3072 frequencies from 15-90 MHz) and as low as 1 ms time resolution.

* Slow Visibility Imaging: in this mode, the entire 352-element array is interferometrically correlated to provide visibilities for imaging at all 3072 frequencies at 10-s time resolution. This is ideal for imaging quiet Sun and slowly-varying emission such as coronal mass ejections and active region variability.

* Fast Visibility Imaging: in this mode, a subset of 48 antennas (chosen to include mainly outer antennas to maintain good spatial resolution) is interferometrically correlated to provide visibilities for imaging at 768 frequencies (96 kHz frequency resolution) at 0.1-s time resolution. This is ideal for imaging rapidly varying emission such as type II and type III bursts as well as many other solar spectral fine structures.

===Inital Data Access===
In its current commissioning state, we try to run the beamformer and imaging pipeline every day in real-time since November 2023 (no latency for beamforming spectrograms and 5-10 min latency for images). Quicklook real-time spectrograms/images can be accessed from http://ovsa.njit.edu/status.php. To access data from previous days, use the following links (replace yyyymmdd with the date you desire):
* Quicklook beamformer total-power spectrograms: http://ovsa.njit.edu/lwa-data/1min_spectra/yyyymmdd/. Check this link for additional daily plots [[Daily OVRO-LWA Beamformer Data]].
* Quicklook multi-frequency movies at 1-min cadence: http://ovsa.njit.edu/lwa-data/1min_images/yyyymmdd/movie_yyyy-mm-dd.html

Note our pipeline processing development is still in the early phase. For example, absolute flux calibrations have not been done for the beamformer spectrograms. Also, artificial effects (including ionospheric refraction effects) are present in the images that cause distortions/shifts. We caution interested users only to consider them for quick-look purposes at this point. Please contact the EOVSA PIs (Dale Gary, Bin Chen) if you intend to use them for science.

===OVRO-LWA Operation Notes===

[[OVRO-LWA Operation Notes]]

== Tohbans ==

[[Trouble Shooting Guide]]

[[Tohban Records]]

[[Owen's Notes]]

[[Caius' Notes]]

[[Tohban EOVSA Imaging Tutorial A-Z]]

[[Tohban OVRO-LWA Imaging Tutorial]]

[[Tohban Guide to Self Calibration and Imaging for EOVSA]]

[[Guide to Upgrade SolarSoft(SSW)]]

[[Star Pointing Notes]]

== VLA Flare List and Publications ==
See [http://www.ovsa.njit.edu/wiki/index.php/VLA_Data_Survey#List_of_Jansky_VLA_Solar_Observations this link] for a list of flare observations made by the [https://science.nrao.edu/facilities/vla/ Karl G. Jansky Very Large Array] (VLA). Below is a partial list of publications that utilize VLA solar data (see also [https://ui.adsabs.harvard.edu/public-libraries/ZwbjpLo9RS-viufWEoQ95Q this NASA/ADS Library]).
* [https://ui.adsabs.harvard.edu/abs/2022ApJ...940..137L/abstract Luo et al. (2022), ApJ, 940, 137] ''Multiple Regions of Nonthermal Quasiperiodic Pulsations during the Impulsive Phase of a Solar Flare''
* [https://ui.adsabs.harvard.edu/abs/2021ApJ...922..134B/abstract Battaglia et al. (2021), ApJ, 922, 134] ''Multiple Electron Acceleration Instances during a Series of Solar Microflares Observed Simultaneously at X-Rays and Microwaves''
* [https://ui.adsabs.harvard.edu/abs/2021ApJ...911....4L/abstract Luo et al. (2021), ApJ, 911, 4] ''Radio Spectral Imaging of an M8.4 Eruptive Solar Flare: Possible Evidence of a Termination Shock''
* [https://ui.adsabs.harvard.edu/abs/2021ApJ...910...40Z/abstract Zhang et al. (2021), ApJ, 910, 40] ''Multiwavelength Observations of the Formation and Eruption of a Complex Filament''
* [https://ui.adsabs.harvard.edu/abs/2020ApJ...904...94S/abstract Sharma et al. (2020), ApJ, 904, 94] ''Radio and X-Ray Observations of Short-lived Episodes of Electron Acceleration in a Solar Microflare''
* [https://ui.adsabs.harvard.edu/abs/2019ApJ...884...63C/abstract Chen et al. (2019), ApJ, 884, 63] ''Radio Spectroscopic Imaging of a Solar Flare Termination Shock: Split-band Feature as Evidence for Shock Compression''
* [https://ui.adsabs.harvard.edu/abs/2019ApJ...872...71Y/abstract Yu & Chen (2019), ApJ, 872, 71] ''Possible Detection of Subsecond-period Propagating Magnetohydrodynamics Waves in Post-reconnection Magnetic Loops during a Two-ribbon Solar Flare''
* [https://ui.adsabs.harvard.edu/abs/2018ApJ...866...62C/abstract Chen et al. (2018), ApJ, 866, 62] ''Magnetic Reconnection Null Points as the Origin of Semirelativistic Electron Beams in a Solar Jet
''
* [https://ui.adsabs.harvard.edu/abs/2017ApJ...848...77W/abstract Wang et al. (2016), ApJ, 848, 77] ''Dynamic Spectral Imaging of Decimetric Fiber Bursts in an Eruptive Solar Flare''
* [https://ui.adsabs.harvard.edu/abs/2015Sci...350.1238C/abstract Chen et al. (2015), Science, 350, 1238] ''Particle acceleration by a solar flare termination shock''
* [https://ui.adsabs.harvard.edu/abs/2014ApJ...794..149C/abstract Chen et al. (2014), ApJ, 794, 149] ''Direct Evidence of an Eruptive, Filament-hosting Magnetic Flux Rope Leading to a Fast Solar Coronal Mass Ejection''
* [https://ui.adsabs.harvard.edu/abs/2013ApJ...763L..21C/abstract Chen et al. (2013), ApJL, 763, 21] ''Tracing Electron Beams in the Sun's Corona with Radio Dynamic Imaging Spectroscopy''

==Radio Data from Around The Heliosphere==
* [http://ovsa.njit.edu//wiki/index.php/Radio_Data_from_Around_the_World#Radio_Data_Access '' Radio Data '']

==Radio Astronomy Lecture Notes==
Here is a link to the [[Radio Astronomy Lecture Notes]] adapted from the Phys728: Radio Astronomy graduate-level course Prof. Dale Gary taught at NJIT until Spring 2019.

OVSA Science Highlights

2025-08-02T13:25:47Z

Binchen: /* Latest Highlights */

==For Authors==

We welcome submissions for all works that utilize OVSA data. Please see [https://docs.google.com/document/d/1ygn7BrU8IKu-6Q00_MCZTeswLZFXOl9TKU342-u_tCU/edit?usp=sharing the Author Guidelines] for submission guidance.

==Latest Highlights==

[[OVSA Science Highlight #1: Microwave Precursor of a Major Solar Eruption]]

OVRO-LWA Operation Notes

2025-08-01T17:06:25Z

Binchen: /* Starting solar beamforming observations */

==Starting solar beamforming observations==
* Log into lwacalim10 using your own account (this is the only node that allows submissions)
* Activate the deployment conda environment
<pre> conda activate deployment </pre>
* Check what schedules are there
<pre>
lwaobserving show-schedule
</pre>
* Submit the schedule for the next 7 days (note that sdf files are written to /tmp/solar_<date>_<time>.sdf and will be owned by you).
<pre>
ipython
cd /home/dgary
import make_solar_sdf
make_solar_sdf.multiday_obs(ndays=7)
</pre>
Note that the make_solar_sdf routine first creates a set of sdf files (the number of files is determined by ndays), defaulting to /tmp/, then submits all of them. If the day has already started when creating the sdf, it will add 15 minutes to the current time for the first sdf.

To make any changes, use the "lwaobserving" suite. Use "lwaobserving --help" and "lwaobserving [function] --help" to see its functionalities and usages.

* Calibrate the beam (if needed, using the same Python session)
<pre>
from mnc import control
con=control.Controller('/opt/devel/dgary/lwa_config_calim_std.yaml')
con.configure_xengine(['dr2'], calibratebeams=True)
</pre>
If the beam is already calibrated, the con.configure_xengine command will say that and return immediately. If for any reason you want to override the current calibration, instead type
<pre>
con.configure_xengine(['dr2'], calibratebeams=True, force=True)
</pre>

==Starting slow and fast visibility recorders ==
* Log into lwacalim10 using your own account
* Check the recorder status by going to http://localhost:5006/LWA_dashboard
* Activate the environment and configure
<pre>
conda activate deployment
ipython
cd /home/pipeline/proj/lwa-shell/mnc_python/
from mnc import control
con=control.Controller('/opt/devel/dgary/lwa_config_calim_std.yaml')
</pre>
* Start the recorders
<pre>
con.start_dr(['drvs', 'drvf'])
</pre>
* Check the recorder status in command line
<pre>
con.status_dr()
</pre>

==Restart slow and fast visibility recorder services (experts only!)==
Occasionally, one would see slow and/or fast images on certain bands showing "No Data" all the time. This is the time to suspect that the recorder services need to be restarted. To check this, do the following:
* Log into lwacalim10 and check the recorder status by going to http://localhost:5006/LWA_dashboard. If the recorder services are okay but not started, they show as "normal, idle." In this case, one can just start the recorders following the previous section. If recorders show up as "shutdown," then we need to restart the recorder services.
* Check if the data are being written to disk. One can run the following script for a given day (format yyyy-mm-dd)
<pre>
source /opt/devel/dgary/check_recording.sh 2024-09-27
</pre>
If all data are being recorded, it would list all the hours of the day that have data. Otherwise, something like the following would be shown
<pre>
ls: cannot access '/lustre/pipeline/slow/32MHz/2024-09-27/': No such file or directory
ls: cannot access '/lustre/pipeline/slow/69MHz/2024-09-27/': No such file or directory
ls: cannot access '/lustre/pipeline/fast/32MHz/2024-09-27/': No such file or directory
ls: cannot access '/lustre/pipeline/fast/69MHz/2024-09-27/': No such file or directory
</pre>
To determine which server node that hosts the recorders, use the following mapping:
<pre>
13 MHz, 50 MHz → lwacalim01
18 MHz, 55 MHz → lwacalim02
23 MHz, 59 MHz → lwacalim03
27 MHz, 64 MHz → lwacalim04
32 MHz, 69 MHz → lwacalim05
36 MHz, 73 MHz → lwacalim06
41 MHz, 78 MHz → lwacalim07
46 MHz, 82 MHz → lwacalim08
</pre>
In the example above, the problem lies in the slow and fast recorders on node lwacalim05. To fix them, do the following
* Log in to the respective node (lwacalim05 in this example) as the "pipeline" user (only a few of us have the privilege)
* Restart the slow and fast services. Each node hosts two slow recorders and two fast recorders. The slow recorders are named dr-vslow-[m1] and dr-vslow-[m2], where m1=2n-1 and m2=2n, with n the node number (5 in this example). Similarly, the fast recorders are named dr-vfast-[m].
<pre>
systemctl --user restart dr-vslow-9
systemctl --user restart dr-vslow-10
systemctl --user restart dr-vfast-9
systemctl --user restart dr-vfast-10
</pre>
Once this is done, check http://localhost:5006/LWA_dashboard again. The recorders in question should show as "normal, idle." The last step is to start the recorders following the steps in the previous section, e.g.,
<pre>
con.start_dr(['drvs', 'drvf'])
</pre>
Don't worry if you see messages such as "'Failed to schedule recording start: Operation starts during a previously scheduled operation'" for recorders that are already working. Pay attention to those weren't working, and they should display something like "'drvs8002': {'sequence_id': '7428a3d67cee11ef80113cecef5ef4c6', 'timestamp': 1727454906.4683754, 'status': 'success', 'response': {'filename': '/lustre/pipeline/slow/'}}".
Lastly, check if the recorders are back and the data are flowing.
<pre>
con.status_dr(['drvs', 'drvf'])
</pre>

==Restart Xengine==
If for some reason the entire Xengine is not working (e.g., the OVRO-LWA system health board shows that they are all red), one can do the following to restart it.
<pre>
lwamnc start-xengine --full
</pre>

==Check/Set ARX attenuator settings==

Under the "deployment" environment
<pre>
> cd /home/pipeline/proj/lwa-shell/mnc_python/
> from mnc import settings
> s = settings.Settings()
> last = s.get_last_settings()
# last is a dictionary that contains the last setting information. The time is in mjd
> print(last)
{'time_loaded': 60607.64228738569, 'user': 'bin.chen', 'filename': '20240922-settingsAll-day.mat'}
> from astropy.time import Time
> Time(last['time_loaded'], format='mjd').isot
Out[25]: '2024-10-24T15:24:53.630'
</pre>

List all the settings:
<pre>
s.list_settings()
</pre>

If last['filename'] != the latest daytime file ("20240922-settingsAll-day.mat" in this case), set it to the latest.
<pre>
settings.update('/home/pipeline/opsdata/20240922-settingsAll-day.mat')
</pre>

==Check bad antennas==
Andrea Isella produces reports of the antenna health at [http://obelix.rice.edu/~ai14/OVRO_LWA/ this link]. The lists can be accessed using the method below on the lwacalim nodes.
<pre>
conda activate deployment
ipython
cd /home/pipeline/proj/lwa-shell/mnc_python/
from mnc import anthealth
badants = anthealth.get_badants('selfcorr')
</pre>

Check the time and antenna list of the latest report
<pre>
from astropy.time import Time
Time(badants[0], format='mjd').isot
print(badants[1])
</pre>

Note that the output antenna list refer to the antenna names, but not the "correlator numbers" or CASA antenna indices.

== Realtime Pipeline and Calim (Slurm) ==

=== Resource ===
Calim cluster
(2024-Sep-19)
* Partition: general (10)
* 48 CPU, 512GByte memory, 2 GPU (RTX A4000, 16GByte)

[[File:Cluster-resource-image.png|700px]]

Slurm full guide: [https://slurm.schedmd.com/quickstart.html]

=== Commands ===
<pre lang="bash">
sinfo # print the overview of the Slurm system
squeue # show the current queue, including the running and queueing jobs, with jobID
scancel <job id> # cancel the (running/queueing) job, the resource will be released
</pre>

Ideally, during solar observation, using the command squeue should get status "R" for solarpipe:

<pre>
squeue -u solarpipe
</pre>

output:
<pre>

JOBID PARTITION NAME USER ST TIME NODES NODELIST(REASON)
6986 solar solarpip solarpip R 6:55:02 7 lwacalim[04-10]
6985 solar solarpip solarpip R 6:55:04 7 lwacalim[04-10]
</pre>

If not, report to the slack ovro-lwa channel.

To restart the pipeline, do:

<pre>
scancel -u solarpipe # !this will kill all task under solarpipe!
</pre>

and

<pre>
sbatch /lustre/peijin/ovro-lwa-solar-ops/runSlurm_solarPipeline.sh slow
sbatch /lustre/peijin/ovro-lwa-solar-ops/runSlurm_solarPipeline.sh fast
</pre>

Making quick-look flare spectrograms and images

2024-10-14T17:26:21Z

Binchen: /* Step 2: Analyze the flare */

This page documents instructions for EOVSA Scientists-on-Duty (SoD) to create quicklook flare spectrograms and movies as part of their daily routines.

== Prerequisites ==

Login into the pipeline machine with your account:

<pre style="font-family:courier">ssh -X <your_user_name>@pipeline</pre>

If your default shell is not bash, enter bash by
<pre style="font-family:courier">bash</pre>

=== Configuring Access to the Interim Database (IDB) ===

To process and calibrate EOVSA raw "Interim" Database (IDB) data, access to the SQL database containing the calibration data is required. Perform the following steps to configure access:

Obtain Database Credentials: Contact Bin Chen to request the <username>, <account_name>, and <password> for database access.

Create a ".netrc" File: Create a ".netrc" file in your home directory ("$HOME") with the following contents, replacing "<username>," "<account_name>," and "<password>" with the actual database credentials:

<pre>machine eovsa-db0.cgb0fabhwkos.us-west-2.rds.amazonaws.com
login <username>
account <account_name>
password <password></pre>

Secure the ".netrc" File: To ensure that the file is only accessible by you, set its permissions to only allow owner read/write:

<pre>chmod 600 ~/.netrc</pre>

=== Set up the Python Environment ===

If the following is not already in your ~/.bashrc file, do the following
<pre style="font-family:courier">alias loadpyenv3.8='source /home/user/.setenv_pyenv38'
export EOVSADBJSON=/common/python/current/EOVSADB.json </pre>

Load the Python 3.8 environment

<pre style="font-family:courier">loadpyenv3.8
ipython --pylab</pre>

== Producing EOVSA quick-look flare spectrograms ==

=== Step 1: Checking Possible flares ===

Verify the possible flares on the daily EOVSA Solar Dynamic Spectrogram, for example:

http://ovsa.njit.edu/browser/?suntoday_date=2024-05-07

[[File:Daily_spec_20240507.png|none|thumb|center|500px|]]

In this example, we see a possible flare that happened around 16:30 UT, which appears as a bright vertical stripe in the daily cross-power dynamic spectrum.

For better visualization and flare time precision, check the higher-resolution dynamic spectra at:

http://ovsa.njit.edu/flaremon/. "XSPYYYYMMDDHHMMSS.png" are the file names you are looking for.

[[File:XSP20240507153014.png|none|thumb|center|500px|]]

Since 2024-May-05, real-time flare detection figures and list are also available at:

http://ovsa.njit.edu/flaremon/FLM20240507.png
http://ovsa.njit.edu/flaremon/flarelist/flarelist_2024-05-07.txt

[[File:FLM20240507.png|none|thumb|center|500px|]]

=== Step 2: Analyze the flare ===

Enter a working directory. We have limited space under /home, so it is better to go to your directory under /data1/.

<pre style="font-family:courier">cd /data1/<your_user_name>/</pre>

Obtain IDB files by providing a time range that encloses the flare. This step will also perform various calibration steps (absolute flux, attenuator gain, and feed rotation), so it may take a while (a few minutes per file). During the course, it will also ask you to confirm the files to be processed. Each IDB file is supposed to be 10-minute long. The naming convention is "IDByyyymmddhhmmdd," with the time indicating the start time of the file.

In Python, enter the following:

<pre style="font-family:courier">from eovsapy import flare_spec as fs
from eovsapy.util import Time </pre>

<pre style="font-family:courier">files = fs.calIDB(Time(['2024-05-07 16:20','2024-05-07 16:35'])) </pre>

<pre style="font-family:courier">The timerange corresponds to these files (will take about 8 minutes to process)
/data1/eovsa/fits/IDB/20240507/IDB20240507162024
/data1/eovsa/fits/IDB/20240507/IDB20240507163024
Do you want to continue? (say no if you want to adjust timerange) [y/n]?y </pre>

The previous step, if successful, will produce a list of IDB files under the current directory
<pre>In [21]: print(files)
['./IDB20240507162024', './IDB20240507163024']</pre>

Inspect the spectrograms and see if all the antennas look okay.

<pre style="font-family:courier">out, spec_tp, spec_xp = fs.inspect(files) </pre>

Two figures will be produced. One two-panel figure shows the median total-power spectrogram across all antennas and a cross-power spectrogram across a set of baselines defined by "uvrange" (default to 45 to 300 m).

Another shows total-power spectrograms for all 16 antennas. (Note the antenna names go from 1 to 16. Ant 14 is the 27-m for calibrations, and Ants 15 and 16 are not yet connected to the system, but will be available soon.)

[[File:Specs_quicklook.jpg|none|thumb|center|500px|]]
[[File:Tpspec_all.jpg|none|thumb|center|500px|]]

To fine-tune the color normalization, you can directly call the plt_quicklook_specs() function by providing spec_tp, spec_xp, and out. Adjust the normalization for the spectrograms using "vmin_tp" and "vmax_tp" for total power and "vmin_xp" and "vmax_xp" for cross power:

<pre style="font-family:courier"> fs.plt_quicklook_specs(spec_tp, spec_xp, out=out, vmin_xp=1., vmax_xp=100., vmin_tp=10., vmax_tp=600.) </pre>

Check the [https://ovsa.njit.edu/wiki/index.php/Expanded_Owens_Valley_Solar_Array#EOVSA_Observing_Log EOVSA Observing Log] for antennas that were not working. We should also check the total-power spectrograms to see if there are any anomalies. In this example, except for Ant 10, all others look okay. However, the observing log says Ant 7 has issues with the Y polarization. Let us exclude both of them using the "ant_str" parameter.

<pre style="font-family:courier"> out, spec_tp, spec_xp = fs.inspect(files, ant_str='ant1-6 ant8-9 ant11-13', vmin_xp=1., vmax_xp=100., vmin_tp=10., vmax_tp=600.) </pre>

Use the output figure to 1) choose the background interval (bgidx), 2) identify the flare peak time, 3) select frequencies for plotting. The box at the top-right of the plot shows the time index/time string, frequency index/frequency string, flux for total power and cross power at the location of your cursor. Move your cursor around and write the information down. For the background interval, I chose time indices from 170 to 200, as they are close to the flare time, but do not appear to have any flare emission. Also, make sure the range does not have strong RFIs. To reduce the potential of large variations, it is advised to select a background period of more than 10 seconds when possible. The parameter "tpk" is the flare peak time found from EOVSA spectrograms. It determines the name of the resulting files (.png and .fits) and the flare_id. In this example, I found the peak time is very close to 2024-05-07T16:29:01. See the snapshot below. Note the flare peak can vary from frequency to frequency. Let us use 10 GHz as the first reference. If the flare signature at 10 GHz is unclear, use 5 GHz as the second reference. The accuracy of the peak time does not need to be down to the second level. Just use your best judgment.

[[File:Specs_quicklook_adj.jpg|none|thumb|center|500px|]]

=== Step 3: Write out final products ===

Now, we are ready to make the final products for the spectrograms using the make_plot() function. To ensure the color scaling and antenna/baseline selection are optimized, the cross-power and total-power spectrograms need to be created separately.

==== Producing final cross-power spectrogram ====

For the median cross-power spectrogram, our previous selections of the antennas should be fine, as it is a median over many baselines. Also, as we advise to our users, the cross-power spectrograms are not supposed to be used for quantitative spectral analysis but only as a reference for, e.g., timing analysis. So small variations in the flux are okay.

<pre style="font-family:courier">f, ax0, ax1 = fs.make_plot(out, bgidx=[170, 200], vmin=0.1, vmax=110, lcfreqs=[120, 190, 270, 350], ant_str='ant1-6 ant8-9 ant11-13', tpk='2024-05-07 16:29:01', spec_type='xp', writefits=True) </pre>

[[File:eovsa.spec_xp.flare_id_20240507162901.png|none|thumb|center|500px|]]

A second background interval can be defined after the flare, if desired. The background will be an interpolation of the two (before and after the flare). e.g., bg2idx=[1000,1010]

In this example, the output files are "eovsa.spec_xp.flare_id_20240507162901.png" and "eovsa.spec_xp.flare_id_20240507162901.fits."

==== Producing final total-power spectrogram ====

For the total-power spectrum, we need to be more careful. The final product is a median over a number of selected antennas. We need to ensure the total-power spectrograms from these selected antennas are consistent with each other. The exact selection is subjective and varies from observer to observer, but one wants to avoid using antennas that are 1) not working, 2) too noisy, or 3) show significant differences from the others. In this example, I chose antennas 1, 4, 5, 12, and 13, based on the total-power spectrograms plot made by flare_spec.inspect().

[[File:Tpspec_ant_selection.jpg|none|thumb|center|500px|]]

<pre style="font-family:courier">f, ax0, ax1 = fs.make_plot(out, bgidx=[170, 200], vmin=1., vmax=200, lcfreqs=[120, 190, 270, 350], ant_str='ant1 ant4 ant5 ant12 ant13', tpk='2024-05-07 16:29:01', spec_type='tp', writefits=True)) </pre>

[[File:eovsa.spec_tp.flare_id_20240507162901.png|none|thumb|center|500px|]]

At the end, copy the .fits file to /common/webplots/events/2024:

<pre style="font-family:courier"> cp eovsa.*.flare_id_20240507162901.* /common/webplots/events/2024/ </pre>

and include the flare in the wiki Flare List:

http://ovsa.njit.edu/wiki/index.php/2024

Making quick-look flare spectrograms and images

2024-10-14T16:25:17Z

Binchen:

This page documents instructions for EOVSA Scientists-on-Duty (SoD) to create quicklook flare spectrograms and movies as part of their daily routines.

== Prerequisites ==

Login into the pipeline machine with your account:

<pre style="font-family:courier">ssh -X <your_user_name>@pipeline</pre>

If your default shell is not bash, enter bash by
<pre style="font-family:courier">bash</pre>

=== Configuring Access to the Interim Database (IDB) ===

To process and calibrate EOVSA raw "Interim" Database (IDB) data, access to the SQL database containing the calibration data is required. Perform the following steps to configure access:

Obtain Database Credentials: Contact Bin Chen to request the <username>, <account_name>, and <password> for database access.

Create a ".netrc" File: Create a ".netrc" file in your home directory ("$HOME") with the following contents, replacing "<username>," "<account_name>," and "<password>" with the actual database credentials:

<pre>machine eovsa-db0.cgb0fabhwkos.us-west-2.rds.amazonaws.com
login <username>
account <account_name>
password <password></pre>

Secure the ".netrc" File: To ensure that the file is only accessible by you, set its permissions to only allow owner read/write:

<pre>chmod 600 ~/.netrc</pre>

=== Set up the Python Environment ===

If the following is not already in your ~/.bashrc file, do the following
<pre style="font-family:courier">alias loadpyenv3.8='source /home/user/.setenv_pyenv38'
export EOVSADBJSON=/common/python/current/EOVSADB.json </pre>

Load the Python 3.8 environment

<pre style="font-family:courier">loadpyenv3.8
ipython --pylab</pre>

== Producing EOVSA quick-look flare spectrograms ==

=== Step 1: Checking Possible flares ===

Verify the possible flares on the daily EOVSA Solar Dynamic Spectrogram, for example:

http://ovsa.njit.edu/browser/?suntoday_date=2024-05-07

[[File:Daily_spec_20240507.png|none|thumb|center|500px|]]

In this example, we see a possible flare that happened around 16:30 UT, which appears as a bright vertical stripe in the daily cross-power dynamic spectrum.

For better visualization and flare time precision, check the higher-resolution dynamic spectra at:

http://ovsa.njit.edu/flaremon/. "XSPYYYYMMDDHHMMSS.png" are the file names you are looking for.

[[File:XSP20240507153014.png|none|thumb|center|500px|]]

Since 2024-May-05, real-time flare detection figures and list are also available at:

http://ovsa.njit.edu/flaremon/FLM20240507.png
http://ovsa.njit.edu/flaremon/flarelist/flarelist_2024-05-07.txt

[[File:FLM20240507.png|none|thumb|center|500px|]]

=== Step 2: Analyze the flare ===

Enter a working directory. We have limited space under /home, so it is better to go to your directory under /data1/.

<pre style="font-family:courier">cd /data1/<your_user_name>/</pre>

Obtain IDB files by providing a time range that encloses the flare. This step will also perform various calibration steps (absolute flux, attenuator gain, and feed rotation), so it may take a while (a few minutes per file). During the course, it will also ask you to confirm the files to be processed. Each IDB file is supposed to be 10-minute long. The naming convention is "IDByyyymmddhhmmdd," with the time indicating the start time of the file.

In Python, enter the following:

<pre style="font-family:courier">from eovsapy import flare_spec as fs
from eovsapy.util import Time </pre>

<pre style="font-family:courier">files = fs.calIDB(Time(['2024-05-07 16:20','2024-05-07 16:35'])) </pre>

<pre style="font-family:courier">The timerange corresponds to these files (will take about 8 minutes to process)
/data1/eovsa/fits/IDB/20240507/IDB20240507162024
/data1/eovsa/fits/IDB/20240507/IDB20240507163024
Do you want to continue? (say no if you want to adjust timerange) [y/n]?y </pre>

The previous step, if successful, will produce a list of IDB files under the current directory
<pre>In [21]: print(files)
['./IDB20240507162024', './IDB20240507163024']</pre>

Inspect the spectrograms and see if all the antennas look okay.

<pre style="font-family:courier">out, spec_tp, spec_xp, time_axis, freq_axis = fs.inspect(files) </pre>

Two figures will be produced. One two-panel figure shows the median total-power spectrogram across all antennas and a cross-power spectrogram across a set of baselines defined by "uvrange" (default to 45 to 300 m).

Another shows total-power spectrograms for all 16 antennas. (Note the antenna names go from 1 to 16. Ant 14 is the 27-m for calibrations, and Ants 15 and 16 are not yet connected to the system, but will be available soon.)

[[File:Specs_quicklook.jpg|none|thumb|center|500px|]]
[[File:Tpspec_all.jpg|none|thumb|center|500px|]]

To fine-tune the color normalization, you can directly call the plt_quicklook_specs() function by providing spec_tp, spec_xp, and out. Adjust the normalization for the spectrograms using "vmin_tp" and "vmax_tp" for total power and "vmin_xp" and "vmax_xp" for cross power:

<pre style="font-family:courier"> fs.plt_quicklook_specs(spec_tp, spec_xp, out=out, vmin_xp=1., vmax_xp=100., vmin_tp=10., vmax_tp=600.) </pre>

Check the [https://ovsa.njit.edu/wiki/index.php/Expanded_Owens_Valley_Solar_Array#EOVSA_Observing_Log EOVSA Observing Log] for antennas that were not working. We should also check the total-power spectrograms to see if there are any anomalies. In this example, except for Ant 10, all others look okay. However, the observing log says Ant 7 has issues with the Y polarization. Let us exclude both of them using the "ant_str" parameter.

<pre style="font-family:courier"> out, spec_tp, spec_xp = fs.inspect(files, ant_str='ant1-6 ant8-9 ant11-13', vmin_xp=1., vmax_xp=100., vmin_tp=10., vmax_tp=600.) </pre>

Use the output figure to 1) choose the background interval (bgidx), 2) identify the flare peak time, 3) select frequencies for plotting. The box at the top-right of the plot shows the time index/time string, frequency index/frequency string, flux for total power and cross power at the location of your cursor. Move your cursor around and write the information down. For the background interval, I chose time indices from 170 to 200, as they are close to the flare time, but do not appear to have any flare emission. Also, make sure the range does not have strong RFIs. To reduce the potential of large variations, it is advised to select a background period of more than 10 seconds when possible. The parameter "tpk" is the flare peak time found from EOVSA spectrograms. It determines the name of the resulting files (.png and .fits) and the flare_id. In this example, I found the peak time is very close to 2024-05-07T16:29:01. See the snapshot below. Note the flare peak can vary from frequency to frequency. Let us use 10 GHz as the first reference. If the flare signature at 10 GHz is unclear, use 5 GHz as the second reference. The accuracy of the peak time does not need to be down to the second level. Just use your best judgment.

[[File:Specs_quicklook_adj.jpg|none|thumb|center|500px|]]

=== Step 3: Write out final products ===

Now, we are ready to make the final products for the spectrograms using the make_plot() function. To ensure the color scaling and antenna/baseline selection are optimized, the cross-power and total-power spectrograms need to be created separately.

==== Producing final cross-power spectrogram ====

For the median cross-power spectrogram, our previous selections of the antennas should be fine, as it is a median over many baselines. Also, as we advise to our users, the cross-power spectrograms are not supposed to be used for quantitative spectral analysis but only as a reference for, e.g., timing analysis. So small variations in the flux are okay.

<pre style="font-family:courier">f, ax0, ax1 = fs.make_plot(out, bgidx=[170, 200], vmin=0.1, vmax=110, lcfreqs=[120, 190, 270, 350], ant_str='ant1-6 ant8-9 ant11-13', tpk='2024-05-07 16:29:01', spec_type='xp', writefits=True) </pre>

[[File:eovsa.spec_xp.flare_id_20240507162901.png|none|thumb|center|500px|]]

A second background interval can be defined after the flare, if desired. The background will be an interpolation of the two (before and after the flare). e.g., bg2idx=[1000,1010]

In this example, the output files are "eovsa.spec_xp.flare_id_20240507162901.png" and "eovsa.spec_xp.flare_id_20240507162901.fits."

==== Producing final total-power spectrogram ====

For the total-power spectrum, we need to be more careful. The final product is a median over a number of selected antennas. We need to ensure the total-power spectrograms from these selected antennas are consistent with each other. The exact selection is subjective and varies from observer to observer, but one wants to avoid using antennas that are 1) not working, 2) too noisy, or 3) show significant differences from the others. In this example, I chose antennas 1, 4, 5, 12, and 13, based on the total-power spectrograms plot made by flare_spec.inspect().

[[File:Tpspec_ant_selection.jpg|none|thumb|center|500px|]]

<pre style="font-family:courier">f, ax0, ax1 = fs.make_plot(out, bgidx=[170, 220], vmin=1., vmax=200, lcfreqs=[120, 190, 270, 350], ant_str='ant1 ant4 ant5 ant12 ant13', tpk='2024-05-07 16:29:01', spec_type='tp', writefits=True)) </pre>

[[File:eovsa.spec_tp.flare_id_20240507162901.png|none|thumb|center|500px|]]

At the end, copy the .fits file to /common/webplots/events/2024:

<pre style="font-family:courier"> cp eovsa.*.flare_id_20240507162901.* /common/webplots/events/2024 </pre>

and include the flare in the wiki Flare List:

http://ovsa.njit.edu/wiki/index.php/2024

Owens Valley Solar Arrays

2024-09-27T17:09:45Z

Binchen: /* Operation Notes */

[[File:Eovsa1.png|border|text-top|800px]]

<big>[http://ovsa.njit.edu/ EOVSA] (Expanded Owens Valley Solar Array) is a solar-dedicated radio interferometer operated by the New Jersey Institute of Technology and serving as a '''National Science Foundation Geospace Facility'''. [[File:NSF.jpg|70px]]
<pre>Operation of EOVSA is supported by the National Science Foundation under Grant No. AGS-2130832. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. </pre>
This wiki serves as the site for EOVSA documentation. </big>

[[File:OVRO-LWA1.png|border|text-top|800px]]

<big>OVRO-LWA (Owens Valley Radio Observatory Long Wavelength Array) is an all-sky imager that has a new solar-dedicated spectroscopic imaging mode. OVRO-LWA is a multi-institutional collaboration led by Caltech. NJIT Solar Radio Group is leading its solar-mode development and science. At the bottom of this page are new links for that facility. </big>

== EOVSA Flare List ==

* [https://ovsa.njit.edu/flarelist Query EOVSA Flare list]
* List of EOVSA flares in separate years: [[2024]], [[2023]], [[2022]], [[2021]], [[2020]], [[2019]], [[2017]]

== Using EOVSA Data ==
* <big>[[EOVSA Data products]]</big>: An introduction to standard EOVSA spectrogram and spectral image products with example scripts for reading and plotting.
* <big>[[EOVSA Data Policy]]</big>: Policy for using EOVSA data products.
* <big>Analysis Software</big>: These are for in-depth use of EOVSA data (from calibrated visibilities) and tools for quantitative analysis.
** [https://github.com/suncasa/suncasa SunCASA] A wrapper around [https://casa.nrao.edu/ CASA (the Common Astronomy Software Applications package)] for synthesis imaging and visualizing solar spectral imaging data. CASA is one of the leading software tool for "supporting the data post-processing needs of the next generation of radio astronomical telescopes such as ALMA and VLA", an international effort led by the [https://public.nrao.edu/ National Radio Astronomy Observatory]. The current version of CASA uses Python (2.7) interface. More information about CASA can be found on [https://casa.nrao.edu/ NRAO's CASA website ]. Note, CASA is available ONLY on UNIX-BASED PLATFORMS (and therefore, so is SunCASA).
** [https://github.com/Gelu-Nita/GSFIT GSFIT] A IDL-widget(GUI)-based spectral fitting package called gsfit, which provides a user-friendly display of EOVSA image cubes and an interface to fast fitting codes (via platform-dependent shared-object libraries).
** [https://github.com/suncasa/pygsfit pyGSFIT] A Python-widget(pyQT)-based spectral fitting package, which provides a user-friendly display of EOVSA image cubes, spatially resolved spectra, and an interface to scipy-based fitting codes.
** [[Spectrogram Software]]
** [[Mapping Software]]
* <big>Data Analysis Guides</big>
** <big>[[EOVSA Data Analysis Tutorial 2022]]</big> and <big>[https://colab.research.google.com/drive/19NQb6Emb9HvKX4QHq9ZYCP3RM6nT7sDL#scrollTo=cLdDVptBGG-X EOVSA Workspace]</big> at [https://sphere.boulder.swri.edu/ SPHERE 2022 Workshop]
** <big>[https://colab.research.google.com/drive/1lSLLxgOG6b8kgu9Sk6kSKvrViyubnXG6?usp=sharing#scrollTo=xbXyyLmCFCGL EOVSA Data Analysis Tutorial at RHESSI 19 Workshop]</big>
** <big>[[EOVSA Data Analysis Tutorial]]</big> at [http://rhessi18.umn.edu/ RHESSI XVIII Workshop]
** [[Self-Calibrating Flare Data]] Example script and guides for self-calibrating EOVSA flare data (to be completed)


**[[IDB flare pipeline]] Tutorial to run the flare pipeline for quicklook images



* <big>EOVSA Modeling Guide</big>
**[[GX Simulator]]

* Other helpful links
** [https://casaguides.nrao.edu CASA Guides]
** [http://www.lmsal.com/solarsoft/ SolarSoft IDL]
** [http://www.atnf.csiro.au/computing/software/miriad/userguide/userhtml.html Miriad Guides]
** [https://sites.google.com/site/fgscodes/ Fast Gyrosynchrotron Codes (Alexey Kuznetsov's website)]
** [[Basic GitHub Tutorial]]


* <big>[[Full Disk Simulations]]</big>
* <big>[[All-Day Synthesis Issues]]</big>
* <big>[[Analyzing Pre-2017 Data]]</big>
* <big>[[Fixing Pipeline Problems pre-2021-Feb-07]]</big>

== EOVSA Documentation ==

* <big>General</big>
** [[Downconversion and Frequency Tuning]]
** [[Dealing with Radio Frequency Interference]]
** [[Switching between 200 MHz and 300 MHz Correlator]]
** [[Observing in "Fast" Mode]]

* <big>Computer-Network</big>
** [[Computing Systems]]
** [[Network]]

* <big>Control System</big>
** [[27-m Antenna Commands]]
** [[Schedule Commands]]
** [[Control Commands]]
** [[Attenuation and Level Control]]

* <big>Hardware</big>
** [[Hardware Overview]]
** [[2.1-m Antennas]]
** [[27-m Antennas]]

* <big>System Software</big>
** [[Calibration Database]]
** [[Stateframe Database]]
** [[Database Maintenance]]
** [[Create CASA measurement sets]]

* <big>Calibration</big>
**[[Calibration Overview]]
**[[Pointing Calibration]]
**[[Total Power Calibration]]
**[[System Gain Calibration]]
**[[Antenna Position]] (Baseline Calibration)
**[[Reference Gain Calibration]]
**[[Daily Gain Calibration]]
**[[Delay Calibration]]
**[[Bandpass Calibration]]
**[[Polarization Calibration]]
**[[Calibrator Survey]]
**[[Practical Calibration Tutorial]]

* <big>[[Starburst]]</big>

== System Software ==

* LabVIEW software
* Python code [https://github.com/dgary50/eovsa Github repository]
* [[Python3 Code Installation]]

== EOVSA Observing Log ==
[[2016 November]]; [[2016 December| December]]

[[2017 January]]; [[2017 February | February]]; [[2017 March | March]]; [[2017 April | April]]; [[2017 May | May]]; [[2017 June | June]];
[[2017 July | July]]; [[2017 August | August]]; [[2017 September | September]]; [[2017 October | October]]; [[2017 November | November]]; [[2017 December | December]]

[[2018 January]]; [[2018 February | February]]; [[2018 March | March]]; [[2018 April | April]]; [[2018 May | May]]; [[2018 June | June]];
[[2018 July | July]]; [[2018 August | August]]; [[2018 September | September]]; [[2018 October | October]]; [[2018 November | November]]; [[2018 December | December]]

[[2019 January]]; [[2019 February | February]]; [[2019 March | March]]; [[2019 April | April]]; [[2019 May | May]]; [[2019 June | June]];
[[2019 July | July]]; [[2019 August | August]]; [[2019 September | September]]; [[2019 October | October]]; [[2019 November | November]]; [[2019 December | December]]

[[2020 January]]; [[2020 February | February]]; [[2020 March | March]]; [[2020 April | April]]; [[2020 May | May]]; [[2020 June | June]];
[[2020 July | July]]; [[2020 August | August]]; [[2020 September | September]]; [[2020 October | October]]; [[2020 November | November]]; [[2020 December | December]]

[[2021 January]]; [[2021 February | February]]; [[2021 March | March]]; [[2021 April | April]]; [[2021 May | May]]; [[2021 June | June]];
[[2021 July | July]]; [[2021 August | August]]; [[2021 September | September]]; [[2021 October | October]]; [[2021 November | November]]; [[2021 December | December]]

[[2022 SQL Outage]]

[[2023 January]]; [[2023 February | February]]; [[2023 March | March]]; [[2023 April | April]]; [[2023 May | May]]; [[2023 June | June]];
[[2023 July | July]]; [[2023 August | August]]; [[2023 September | September]]; [[2023 October | October]]; [[2023 November | November]]; [[2023 December | December]]

[[2024 January]]; [[2024 February | February]]; [[2024 March | March]];[[2024 April | April]];[[2024 May |May]]; [[2024 June | June]]; [[2024 July | July]]; [[2024 August | August]];
[[2024 September | September]]

== SoD Observing Logs ==
* See [https://docs.google.com/document/d/1_iGnMRRrvb85Z0vT8-LzgQmCOKDSATEuQ0vTsn2C-dc/edit?usp=sharing SoD Routines] for detailed instructions for Scientist-on-Duty routines.
* 2024 [https://docs.google.com/document/d/1QDWw5y4HpcE7CSpzXwftMqQT4FDgNJj-6fRrgWrqdug/edit?usp=sharing May (and before that)], [https://docs.google.com/document/d/1Rh2gYBV2E454xVYEv8jx5IXKd1N2Z05ns4dhI2XCE08/edit?usp=sharing June], [https://docs.google.com/document/d/1beUpp6rgwjqSxKbuHzXIR9hhPrGyi0j-SjtEIeav9Vg/edit?usp=sharing July], [https://docs.google.com/document/d/1pSzUXW5gd-4cZAR-gglTUVM_J2UHMa4wYJ2AzD4cdEo/edit?usp=sharing August], [https://docs.google.com/document/d/18pArAP0kRDhXHbty_y3TtrygmWkC2oLn-UD7njIpRIo/edit?usp=sharing September], October, November, December

== Tohbans ==

[[Trouble Shooting Guide]]

[[Tohban Records]]

[[Owen's Notes]]

[[Caius' Notes]]

[[Tohban EOVSA Imaging Tutorial A-Z]]

[[Tohban OVRO-LWA Imaging Tutorial]]

[[Tohban Guide to Self Calibration and Imaging for EOVSA]]

[[Guide to Upgrade SolarSoft(SSW)]]

== EOVSA Publications ==
Here is a (partial) list of publications that utilize EOVSA data. See also the collection of EOVSA publications at [https://ui.adsabs.harvard.edu/public-libraries/eQ7HfPkySqydu-B8BCt6QQ this NASA/ADS Library].
; 2024
: Collier, H., Hayes, L. A., Yu, S., Battaglia, A. F., Ashfield, W., Polito, V., Harra, L. K., & Krucker, S. (2024), arXiv e-prints, arXiv:2402.10546. [https://ui.adsabs.harvard.edu/abs/2024arXiv240210546C “Localising pulsations in the hard X-ray and microwave emission of an X-class flare”]
: Saqri, J., Veronig, A. M., Battaglia, A. F., Dickson, E. C. M., Gary, D. E., & Krucker, S. (2024), Astronomy and Astrophysics, 683, A41. [https://ui.adsabs.harvard.edu/abs/2024A&A...683A..41S "Efficiency of solar microflares in accelerating electrons when rooted in a sunspot"]
; 2023
: Tan, B., Yan, Y., Huang, J., Zhang, Y., Tan, C., & Zhu, X. (2023), Advances in Space Research, 72, 5563. [https://ui.adsabs.harvard.edu/abs/2023AdSpR..72.5563T "The physics of solar spectral imaging observations in dm-cm wavelengths and the application on space weather"]

: Li, D., Li, Z., Shi, F., Su, Y., Chen, W., Yu, F., Li, C., Qiu, Y., Huang, Y., & Ning, Z. (2023), Astronomy and Astrophysics, 680, L15. [https://ui.adsabs.harvard.edu/abs/2023A&A...680L..15L "Observational signature of continuously operating drivers of decayless kink oscillation"]

: Wang, M., Chen, B., Yu, S., Gary, D. E., Lee, J., Wang, H., & Cohen, C. (2023), The Astrophysical Journal, 954, 32. [https://ui.adsabs.harvard.edu/abs/2023ApJ...954...32W "The Solar Origin of an In Situ Type III Radio Burst Event"]

: Gary, D. E. (2023), Annual Review of Astronomy and Astrophysics, 61, 427. [https://ui.adsabs.harvard.edu/abs/2023ARA&A..61..427G "New Insights from Imaging Spectroscopy of Solar Radio Emission"]

: Nita, G. M., Fleishman, G. D., Kuznetsov, A. A., Anfinogentov, S. A., Stupishin, A. G., Kontar, E. P., Schonfeld, S. J., Klimchuk, J. A., & Gary, D. E. (2023), The Astrophysical Journal Supplement Series, 267, 6. [https://ui.adsabs.harvard.edu/abs/2023ApJS..267....6N "Data-constrained Solar Modeling with GX Simulator"]

: Song, D.-C., Tian, J., Li, Y., Ding, M. D., Su, Y., Yu, S., Hong, J., Qiu, Y., Rao, S., Liu, X., Li, Q., Chen, X., Li, C., & Fang, C. (2023), The Astrophysical Journal, 952, L6. [https://ui.adsabs.harvard.edu/abs/2023ApJ...952L...6S "Spectral Observations and Modeling of a Solar White-light Flare Observed by CHASE"]

: Mondal, S., Chen, B., & Yu, S. (2023), The Astrophysical Journal, 949, 56. [https://ui.adsabs.harvard.edu/abs/2023ApJ...949...56M "Multifrequency Microwave Imaging of Weak Transients from the Quiet Solar Corona"]

: Kontar, E. P., Emslie, A. G., Motorina, G. G., & Dennis, B. R. (2023), The Astrophysical Journal, 947, L13. [https://ui.adsabs.harvard.edu/abs/2023ApJ...947L..13K "The Efficiency of Electron Acceleration during the Impulsive Phase of a Solar Flare"]

: Saqri, J., Veronig, A. M., Dickson, E. C. M., Podladchikova, T., Warmuth, A., Xiao, H., Gary, D. E., Battaglia, A. F., & Krucker, S. (2023), Astronomy and Astrophysics, 672, A23. [https://ui.adsabs.harvard.edu/abs/2023A&A...672A..23S "Multi-point study of the energy release and impulsive CME dynamics in an eruptive C7 flare"]
; 2022

: Kou, Y., Cheng, X., Wang, Y., Yu, S., Chen, B., Kontar, E. P., & Ding, M. (2022), Nature Communications, 13, 7680. [https://ui.adsabs.harvard.edu/abs/2022NatCo..13.7680K "Microwave imaging of quasi-periodic pulsations at flare current sheet"]

: Chertok, I. M. (2022), Monthly Notices of the Royal Astronomical Society, 517, 2709. [https://ui.adsabs.harvard.edu/abs/2022MNRAS.517.2709C "On some features of the solar proton event on 2021 October 28 - GLE73"]

: Lörinčík, J., Polito, V., De Pontieu, B., Yu, S., & Freij, N. (2022), Frontiers in Astronomy and Space Sciences, 9, 334. [https://ui.adsabs.harvard.edu/abs/2022FrASS...940945L "Rapid variations of Si IV spectra in a flare observed by interface region imaging spectrograph at a sub-second cadence"]

: Klein, K.-L., Musset, S., Vilmer, N., Briand, C., Krucker, S., Francesco Battaglia, A., Dresing, N., Palmroos, C., & Gary, D. E. (2022), Astronomy and Astrophysics, 663, A173. [https://ui.adsabs.harvard.edu/abs/2022A&A...663A.173K "The relativistic solar particle event on 28 October 2021: Evidence of particle acceleration within and escape from the solar corona"]

: Fleishman, G. D., Nita, G. M., Chen, B., Yu, S., & Gary, D. E. (2022), Nature, 606, 674. [https://ui.adsabs.harvard.edu/abs/2022Natur.606..674F "Solar flare accelerates nearly all electrons in a large coronal volume"]

: Li, X., Guo, F., Chen, B., Shen, C., & Glesener, L. (2022), The Astrophysical Journal, 932, 92. [https://ui.adsabs.harvard.edu/abs/2022ApJ...932...92L "Modeling Electron Acceleration and Transport in the Early Impulsive Phase of the 2017 September 10th Solar Flare"]

: Zhang, J., Chen, B., Yu, S., Tian, H., Wei, Y., Chen, H., Tan, G., Luo, Y., & Chen, X. (2022), The Astrophysical Journal, 932, 53. [https://ui.adsabs.harvard.edu/abs/2022ApJ...932...53Z "Implications for Additional Plasma Heating Driving the Extreme-ultraviolet Late Phase of a Solar Flare with Microwave Imaging Spectroscopy"]

: Liu, N., Jing, J., Xu, Y., & Wang, H. (2022), The Astrophysical Journal, 930, 154. [https://ui.adsabs.harvard.edu/abs/2022ApJ...930..154L "Multi-instrument Comparative Study of Temperature, Number Density, and Emission Measure during the Precursor Phase of a Solar Flare"]

: López, F. M., Giménez de Castro, C. G., Mandrini, C. H., Simões, P. J. A., Cristiani, G. D., Gary, D. E., Francile, C., & Démoulin, P. (2022), Astronomy and Astrophysics, 657, A51. [https://ui.adsabs.harvard.edu/abs/2022A&A...657A..51L "A solar flare driven by thermal conduction observed in mid-infrared"]

: Unverferth, J., & Longcope, D. (2021), The Astrophysical Journal, 923, 248. [https://ui.adsabs.harvard.edu/abs/2021ApJ...923..248U "Examining Flux Tube Interactions as a Cause of Sub-alfvénic Outflow"]
;2021

: Wei, Y., Chen, B., Yu, S., Wang, H., Jing, J., & Gary, D. E. (2021), The Astrophysical Journal, 923, 213. [https://ui.adsabs.harvard.edu/abs/2021ApJ...923..213W "Coronal Magnetic Field Measurements along a Partially Erupting Filament in a Solar Flare"]

: Jing, J., Inoue, S., Lee, J., Li, Q., Nita, G. M., Xu, Y., Liu, C., Gary, D. E., & Wang, H. (2021), The Astrophysical Journal, 922, 108. [https://ui.adsabs.harvard.edu/abs/2021ApJ...922..108J "Understanding the Initiation of the M2.4 Flare on 2017 July 14"]

: Battaglia, A. F., Saqri, J., Massa, P., Perracchione, E., Dickson, E. C. M., Xiao, H., Veronig, A. M., Warmuth, A., Battaglia, M., Hurford, G. J., Meuris, A., Limousin, O., Etesi, L., Maloney, S. A., Schwartz, R. A., Kuhar, M., Schuller, F., Senthamizh Pavai, V., Musset, S., Ryan, D. F., Kleint, L., Piana, M., Massone, A. M., Benvenuto, F., Sylwester, J., Litwicka, M., Stȩślicki, M., Mrozek, T., Vilmer, N., Fárník, F., Kašparová, J., Mann, G., Gallagher, P. T., Dennis, B. R., Csillaghy, A., Benz, A. O., & Krucker, S. (2021), Astronomy and Astrophysics, 656, A4. [https://ui.adsabs.harvard.edu/abs/2021A&A...656A...4B "STIX X-ray microflare observations during the Solar Orbiter commissioning phase"]

: Shaik, S. B., & Gary, D. E. (2021), The Astrophysical Journal, 919, 44. [https://ui.adsabs.harvard.edu/abs/2021ApJ...919...44S "Implications of Flat Optically Thick Microwave Spectra in Solar Flares for Source Size and Morphology"]

: Kocharov, L., Omodei, N., Mishev, A., Pesce-Rollins, M., Longo, F., Yu, S., Gary, D. E., Vainio, R., & Usoskin, I. (2021), The Astrophysical Journal, 915, 12. [https://ui.adsabs.harvard.edu/abs/2021ApJ...915...12K "Multiple Sources of Solar High-energy Protons"]

: Chen, B., Battaglia, M., Krucker, S., Reeves, K. K., & Glesener, L. (2021), The Astrophysical Journal, 908, L55. [https://ui.adsabs.harvard.edu/abs/2021ApJ...908L..55C "Energetic Electron Distribution of the Coronal Acceleration Region: First Results from Joint Microwave and Hard X-Ray Imaging Spectroscopy"]

: Chhabra, S., Gary, D. E., Hallinan, G., Anderson, M. M., Chen, B., Greenhill, L. J., & Price, D. C. (2021), The Astrophysical Journal, 906, 132. [https://ui.adsabs.harvard.edu/abs/2021ApJ...906..132C "Imaging Spectroscopy of CME-associated Solar Radio Bursts using OVRO-LWA"]
;2020 and earlier

: Reeves, K. K., Polito, V., Chen, B., Galan, G., Yu, S., Liu, W., & Li, G. (2020), The Astrophysical Journal, 905, 165. [https://ui.adsabs.harvard.edu/abs/2020ApJ...905..165R "Hot Plasma Flows and Oscillations in the Loop-top Region During the 2017 September 10 X8.2 Solar Flare"]

: Nindos, A. (2020), Frontiers in Astronomy and Space Sciences, 7, 57. [https://ui.adsabs.harvard.edu/abs/2020FrASS...7...57N "Incoherent Solar Radio Emission"]

: Yu, S., Chen, B., Reeves, K. K., Gary, D. E., Musset, S., Fleishman, G. D., Nita, G. M., & Glesener, L. (2020), The Astrophysical Journal, 900, 17. [https://ui.adsabs.harvard.edu/abs/2020ApJ...900...17Y "Magnetic Reconnection during the Post-impulsive Phase of a Long-duration Solar Flare: Bidirectional Outflows as a Cause of Microwave and X-Ray Bursts"]

: Chen, B., Yu, S., Reeves, K. K., & Gary, D. E. (2020), The Astrophysical Journal, 895, L50. [https://ui.adsabs.harvard.edu/abs/2020ApJ...895L..50C "Microwave Spectral Imaging of an Erupting Magnetic Flux Rope: Implications for the Standard Solar Flare Model in Three Dimensions"]

: Kuroda, N., Fleishman, G. D., Gary, D. E., Nita, G. M., Chen, B., & Yu, S. (2020), Frontiers in Astronomy and Space Sciences, 7, 22. [https://ui.adsabs.harvard.edu/abs/2020FrASS...7...22K "Evolution of Flare-accelerated Electrons Quantified by Spatially Resolved Analysis"]

: Glesener, L., Krucker, S., Duncan, J., Hannah, I. G., Grefenstette, B. W., Chen, B., Smith, D. M., White, S. M., & Hudson, H. (2020), The Astrophysical Journal, 891, L34. [https://ui.adsabs.harvard.edu/abs/2020ApJ...891L..34G "Accelerated Electrons Observed Down to <7 keV in a NuSTAR Solar Microflare"]

: Karlický, M., Chen, B., Gary, D. E., Kašparová, J., & Rybák, J. (2020), The Astrophysical Journal, 889, 72. [https://ui.adsabs.harvard.edu/abs/2020ApJ...889...72K "Drifting Pulsation Structure at the Very Beginning of the 2017 September 10 Limb Flare"]

: Fleishman, G. D., Gary, D. E., Chen, B., Kuroda, N., Yu, S., & Nita, G. M. (2020), Science, 367, 278. [https://ui.adsabs.harvard.edu/abs/2020Sci...367..278F "Decay of the coronal magnetic field can release sufficient energy to power a solar flare"]

: Chen, B., Shen, C., Gary, D. E., Reeves, K. K., Fleishman, G. D., Yu, S., Guo, F., Krucker, S., Lin, J., Nita, G. M., & Kong, X. (2020), Nature Astronomy, 4, 1140. [https://ui.adsabs.harvard.edu/abs/2020NatAs...4.1140C "Measurement of magnetic field and relativistic electrons along a solar flare current sheet"]

: Lee, J. (2018), Journal of Astronomy and Space Sciences, 35, 211. [https://ui.adsabs.harvard.edu/abs/2018JASS...35..211L "Analysis of Solar Microwave Burst Spectrum, I. Nonuniform Magnetic Field"]

: Gary, D. E., Bastian, T. S., Chen, B., Fleishman, G. D., & Glesener, L. (2018), Science with a Next Generation Very Large Array, 517, 99. [https://ui.adsabs.harvard.edu/abs/2018ASPC..517...99G "Radio Observations of Solar Flares"]

: Polito, V., Dudík, J., Kašparová, J., Dzifčáková, E., Reeves, K. K., Testa, P., & Chen, B. (2018), The Astrophysical Journal, 864, 63. [https://ui.adsabs.harvard.edu/abs/2018ApJ...864...63P "Broad Non-Gaussian Fe XXIV Line Profiles in the Impulsive Phase of the 2017 September 10 X8.3-class Flare Observed by Hinode/EIS"]

: Gary, D. E., Chen, B., Dennis, B. R., Fleishman, G. D., Hurford, G. J., Krucker, S., McTiernan, J. M., Nita, G. M., Shih, A. Y., White, S. M., & Yu, S. (2018), The Astrophysical Journal, 863, 83. [https://ui.adsabs.harvard.edu/abs/2018ApJ...863...83G "Microwave and Hard X-Ray Observations of the 2017 September 10 Solar Limb Flare"]

: Fleishman, G. D., Nita, G. M., Kuroda, N., Jia, S., Tong, K., Wen, R. R., & Zhizhuo, Z. (2018), The Astrophysical Journal, 859, 17. [https://ui.adsabs.harvard.edu/abs/2018ApJ...859...17F "Revealing the Evolution of Non-thermal Electrons in Solar Flares Using 3D Modeling"]

: Kuroda, N., Gary, D. E., Wang, H., Fleishman, G. D., Nita, G. M., & Jing, J. (2018), The Astrophysical Journal, 852, 32. [https://ui.adsabs.harvard.edu/abs/2018ApJ...852...32K "Three-dimensional Forward-fit Modeling of the Hard X-Ray and Microwave Emissions of the 2015 June 22 M6.5 Flare"]

: Wang, H., Liu, C., Ahn, K., Xu, Y., Jing, J., Deng, N., Huang, N., Liu, R., Kusano, K., Fleishman, G. D., Gary, D. E., & Cao, W. (2017), Nature Astronomy, 1, 0085. [https://ui.adsabs.harvard.edu/abs/2017NatAs...1E..85W "High-resolution observations of flare precursors in the low solar atmosphere"]

: Nita, G. M., Hickish, J., MacMahon, D., & Gary, D. E. (2016), Journal of Astronomical Instrumentation, 5, 1641009-7366. [https://ui.adsabs.harvard.edu/abs/2016JAI.....541009N "EOVSA Implementation of a Spectral Kurtosis Correlator for Transient Detection and Classification"]

: Nita, G. M., & Gary, D. E. (2016), Journal of Geophysical Research (Space Physics), 121, 7353. [https://ui.adsabs.harvard.edu/abs/2016JGRA..121.7353N "Measurement of duration and signal-to-noise ratio of astronomical transients using a Spectral Kurtosis spectrometer"]

: Wang, Z., Gary, D. E., Fleishman, G. D., & White, S. M. (2015), The Astrophysical Journal, 805, 93. [https://ui.adsabs.harvard.edu/abs/2015ApJ...805...93W "Coronal Magnetography of a Simulated Solar Active Region from Microwave Imaging Spectropolarimetry"]

: Gary, D. E., Fleishman, G. D., & Nita, G. M. (2013), Solar Physics, 288, 549. [https://ui.adsabs.harvard.edu/abs/2013SoPh..288..549G "Magnetography of Solar Flaring Loops with Microwave Imaging Spectropolarimetry"]

== VLA Flare List and Publications ==
See [http://www.ovsa.njit.edu/wiki/index.php/VLA_Data_Survey#List_of_Jansky_VLA_Solar_Observations this link] for a list of flare observations made by the [https://science.nrao.edu/facilities/vla/ Karl G. Jansky Very Large Array] (VLA). Below is a partial list of publications that utilize VLA solar data (see also [https://ui.adsabs.harvard.edu/public-libraries/ZwbjpLo9RS-viufWEoQ95Q this NASA/ADS Library]).
* [https://ui.adsabs.harvard.edu/abs/2022ApJ...940..137L/abstract Luo et al. (2022), ApJ, 940, 137] ''Multiple Regions of Nonthermal Quasiperiodic Pulsations during the Impulsive Phase of a Solar Flare''
* [https://ui.adsabs.harvard.edu/abs/2021ApJ...922..134B/abstract Battaglia et al. (2021), ApJ, 922, 134] ''Multiple Electron Acceleration Instances during a Series of Solar Microflares Observed Simultaneously at X-Rays and Microwaves''
* [https://ui.adsabs.harvard.edu/abs/2021ApJ...911....4L/abstract Luo et al. (2021), ApJ, 911, 4] ''Radio Spectral Imaging of an M8.4 Eruptive Solar Flare: Possible Evidence of a Termination Shock''
* [https://ui.adsabs.harvard.edu/abs/2021ApJ...910...40Z/abstract Zhang et al. (2021), ApJ, 910, 40] ''Multiwavelength Observations of the Formation and Eruption of a Complex Filament''
* [https://ui.adsabs.harvard.edu/abs/2020ApJ...904...94S/abstract Sharma et al. (2020), ApJ, 904, 94] ''Radio and X-Ray Observations of Short-lived Episodes of Electron Acceleration in a Solar Microflare''
* [https://ui.adsabs.harvard.edu/abs/2019ApJ...884...63C/abstract Chen et al. (2019), ApJ, 884, 63] ''Radio Spectroscopic Imaging of a Solar Flare Termination Shock: Split-band Feature as Evidence for Shock Compression''
* [https://ui.adsabs.harvard.edu/abs/2019ApJ...872...71Y/abstract Yu & Chen (2019), ApJ, 872, 71] ''Possible Detection of Subsecond-period Propagating Magnetohydrodynamics Waves in Post-reconnection Magnetic Loops during a Two-ribbon Solar Flare''
* [https://ui.adsabs.harvard.edu/abs/2018ApJ...866...62C/abstract Chen et al. (2018), ApJ, 866, 62] ''Magnetic Reconnection Null Points as the Origin of Semirelativistic Electron Beams in a Solar Jet
''
* [https://ui.adsabs.harvard.edu/abs/2017ApJ...848...77W/abstract Wang et al. (2016), ApJ, 848, 77] ''Dynamic Spectral Imaging of Decimetric Fiber Bursts in an Eruptive Solar Flare''
* [https://ui.adsabs.harvard.edu/abs/2015Sci...350.1238C/abstract Chen et al. (2015), Science, 350, 1238] ''Particle acceleration by a solar flare termination shock''
* [https://ui.adsabs.harvard.edu/abs/2014ApJ...794..149C/abstract Chen et al. (2014), ApJ, 794, 149] ''Direct Evidence of an Eruptive, Filament-hosting Magnetic Flux Rope Leading to a Fast Solar Coronal Mass Ejection''
* [https://ui.adsabs.harvard.edu/abs/2013ApJ...763L..21C/abstract Chen et al. (2013), ApJL, 763, 21] ''Tracing Electron Beams in the Sun's Corona with Radio Dynamic Imaging Spectroscopy''

==Radio Data from Around The Heliosphere==
* [http://ovsa.njit.edu//wiki/index.php/Radio_Data_from_Around_the_World#Radio_Data_Access '' Radio Data '']

=OVRO-LWA Solar-Dedicated Spectroscopic Imager=
The OVRO-LWA (Owens Valley Radio Observatory Long Wavelength Array) has recently been upgraded to include a solar-dedicated beam and two solar imaging modes (slow visibilities of 352 antennas with a 10-s cadence, and fast visibilities of 48 antennas with a 0.1-s cadence). The large collecting area and excellent calibration provide unprecedented high-sensitivity imaging of the quiet Sun and bursts. The array is currently in commissioning and observations are not yet continuous, but they are becoming more so. See the daily realtime data at http://ovsa.njit.edu/status.php for '''real-time display of the spectrogram and a selection of images''', both updated on a 1-min cadence.

==Solar-Dedicated Modes==
===Beamformer===
The beamformer uses the 256 core antennas to form a synthesized beam of more than 1 degree in size that tracks the Sun from sunrise to sunset. This permits a continuous record of the full-Stokes total flux (without spatial resolution) of the Sun (a dynamic spectrum) with 24 kHz frequency resolution (3072 frequencies from 15-90 MHz) and as low as 1 ms time resolution.

===Slow Visibility Imaging===
In this mode, the entire 352-element array is interferometrically correlated to provide visibilities for imaging at all 3072 frequencies at 10-s time resolution. This is ideal for imaging quiet Sun and slowly-varying emission such as coronal mass ejections and active region variability.

===Fast Visibility Imaging===
In this mode, a subset of 48 antennas (chosen to include mainly outer antennas to maintain good spatial resolution) is interferometrically correlated to provide visibilities for imaging at 768 frequencies (96 kHz frequency resolution) at 0.1-s time resolution. This is ideal for imaging rapidly varying emission such as type II and type III bursts as well as many other solar spectral fine structures.

==Inital Data Access==
In its current commissioning state, we try to run the beamformer and imaging pipeline every day in real-time since November 2023 (no latency for beamforming spectrograms and 5-10 min latency for images). Quicklook real-time spectrograms/images can be accessed from http://ovsa.njit.edu/status.php. To access data from previous days, use the following links (replace yyyymmdd with the date you desire):
* Quicklook beamformer total-power spectrograms: http://ovsa.njit.edu/lwa-data/1min_spectra/yyyymmdd/. Check this link for additional daily plots [[Daily OVRO-LWA Beamformer Data]].
* Quicklook multi-frequency movies at 1-min cadence: http://ovsa.njit.edu/lwa-data/1min_images/yyyymmdd/movie_yyyy-mm-dd.html

Note our pipeline processing development is still in the early phase. For example, absolute flux calibrations have not been done for the beamformer spectrograms. Also, artificial effects (including ionospheric refraction effects) are present in the images that cause distortions/shifts. We caution interested users only to consider them for quick-look purposes at this point. Please contact the EOVSA PIs (Dale Gary, Bin Chen) if you intend to use them for science.

==Operation Notes==
===Starting solar beamforming observations===
* Log into lwacalim10 (this is the only node that allows submissions)
* Activate the deployment conda environment
<pre> conda activate deployment </pre>
* Check what schedules are there
<pre>
lwaobserving show-schedule
</pre>
* Submit the schedule for the next 7 days (note that sdf files are written to /tmp/solar_<date>_<time>.sdf and will be owned by you).
<pre>
ipython
cd /home/dgary
import make_solar_sdf
make_solar_sdf.multiday_obs(ndays=7)
</pre>
* Calibrate the beam (if needed, using the same Python session)
<pre>
from mnc import control
con=control.Controller('/opt/devel/dgary/lwa_config_calim_std.yaml')
con.configure_xengine(['dr2'], calibratebeams=True)
</pre>
If the beam is already calibrated, the con.configure_xengine command will say that and return immediately. If for any reason you want to override the current calibration, instead type
<pre>
con.configure_xengine(['dr2'], calibratebeams=True, force=True)
</pre>

===Starting slow and fast visibility recorders ===
* Log into lwacalim10
* Check the recorder status by going to http://localhost:5006/LWA_dashboard
* Activate the environment and configure
<pre>
conda activate deployment
ipython
cd /home/pipeline/proj/lwa-shell/mnc_python/
from mnc import control
con=control.Controller('/opt/devel/dgary/lwa_config_calim_std.yaml')
</pre>
* Start the recorders
<pre>
con.start_dr(['drvs', 'drfv'])
</pre>
* Check the recorder status in command line
<pre>
con.status_dr()
</pre>

===Restart slow and fast visibility recorder services (experts only!)===
Occasionally, one would see slow and/or fast images on certain bands showing "No Data" all the time. This is the time to suspect that the recorder services need to be restarted. To check this, do the following:
* Log into lwacalim10 and check the recorder status by going to http://localhost:5006/LWA_dashboard. Recorders in question may show up as "Shutdown."
* Check if the data are being written to disk. One can run the following script for a given day (format yyyy-mm-dd)
<pre>
source /opt/devel/dgary/check_recording.sh 2024-09-27
</pre>
If all data are being recorded, it would list all the hours of the day that have data. Otherwise, something like the following would be shown
<pre>
ls: cannot access '/lustre/pipeline/slow/32MHz/2024-09-27/': No such file or directory
ls: cannot access '/lustre/pipeline/slow/69MHz/2024-09-27/': No such file or directory
ls: cannot access '/lustre/pipeline/fast/32MHz/2024-09-27/': No such file or directory
ls: cannot access '/lustre/pipeline/fast/69MHz/2024-09-27/': No such file or directory
</pre>
To determine which server node that hosts the recorders, use the following mapping:
<pre>
13 MHz, 50 MHz → lwacalim01
18 MHz, 55 MHz → lwacalim02
23 MHz, 59 MHz → lwacalim03
27 MHz, 64 MHz → lwacalim04
32 MHz, 69 MHz → lwacalim05
36 MHz, 73 MHz → lwacalim06
41 MHz, 78 MHz → lwacalim07
46 MHz, 82 MHz → lwacalim08
</pre>
In the example above, the problem lies in the slow and fast recorders on node lwacalim05. To fix them, do the following
* Log in to the respective node (lwacalim05 in this example) as the "pipeline" user (only a few of us have the privilege)
* Restart the slow and fast services. Each node hosts two slow recorders and two fast recorders. The slow recorders are named dr-vslow-[m1] and dr-vslow-[m2], where m1=2n-1 and m2=2n, with n the node number (5 in this example). Similarly, the fast recorders are named dr-vfast-[m].
<pre>
systemctl --user restart dr-vslow-9
systemctl --user restart dr-vslow-10
systemctl --user restart dr-vfast-9
systemctl --user restart dr-vfast-10
</pre>
Once this is done, check http://localhost:5006/LWA_dashboard again. The recorders in question should show as "normal, idle." The last step is to start the recorders following the steps in the previous section, e.g.,
<pre>
con.start_dr(['drvs', 'drvf'])
</pre>
Don't worry if you see messages such as "'Failed to schedule recording start: Operation starts during a previously scheduled operation'" for recorders that are already working. Pay attention to those weren't working, and they should display something like "'drvs8002': {'sequence_id': '7428a3d67cee11ef80113cecef5ef4c6', 'timestamp': 1727454906.4683754, 'status': 'success', 'response': {'filename': '/lustre/pipeline/slow/'}}".
Lastly, check if the recorders are back and the data are flowing.
<pre>
con.status_dr(['drvs', 'drvf'])
</pre>

Owens Valley Solar Arrays

2024-09-26T23:00:13Z

Binchen: /* Starting solar beamforming observations */

[[File:Eovsa1.png|border|text-top|800px]]

<big>[http://ovsa.njit.edu/ EOVSA] (Expanded Owens Valley Solar Array) is a solar-dedicated radio interferometer operated by the New Jersey Institute of Technology and serving as a '''National Science Foundation Geospace Facility'''. [[File:NSF.jpg|70px]]
<pre>Operation of EOVSA is supported by the National Science Foundation under Grant No. AGS-2130832. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. </pre>
This wiki serves as the site for EOVSA documentation. </big>

[[File:OVRO-LWA1.png|border|text-top|800px]]

<big>OVRO-LWA (Owens Valley Radio Observatory Long Wavelength Array) is an all-sky imager that has a new solar-dedicated spectroscopic imaging mode. OVRO-LWA is a multi-institutional collaboration led by Caltech. NJIT Solar Radio Group is leading its solar-mode development and science. At the bottom of this page are new links for that facility. </big>

== EOVSA Flare List ==

* [https://ovsa.njit.edu/flarelist Query EOVSA Flare list]
* List of EOVSA flares in separate years: [[2024]], [[2023]], [[2022]], [[2021]], [[2020]], [[2019]], [[2017]]

== Using EOVSA Data ==
* <big>[[EOVSA Data products]]</big>: An introduction to standard EOVSA spectrogram and spectral image products with example scripts for reading and plotting.
* <big>[[EOVSA Data Policy]]</big>: Policy for using EOVSA data products.
* <big>Analysis Software</big>: These are for in-depth use of EOVSA data (from calibrated visibilities) and tools for quantitative analysis.
** [https://github.com/suncasa/suncasa SunCASA] A wrapper around [https://casa.nrao.edu/ CASA (the Common Astronomy Software Applications package)] for synthesis imaging and visualizing solar spectral imaging data. CASA is one of the leading software tool for "supporting the data post-processing needs of the next generation of radio astronomical telescopes such as ALMA and VLA", an international effort led by the [https://public.nrao.edu/ National Radio Astronomy Observatory]. The current version of CASA uses Python (2.7) interface. More information about CASA can be found on [https://casa.nrao.edu/ NRAO's CASA website ]. Note, CASA is available ONLY on UNIX-BASED PLATFORMS (and therefore, so is SunCASA).
** [https://github.com/Gelu-Nita/GSFIT GSFIT] A IDL-widget(GUI)-based spectral fitting package called gsfit, which provides a user-friendly display of EOVSA image cubes and an interface to fast fitting codes (via platform-dependent shared-object libraries).
** [https://github.com/suncasa/pygsfit pyGSFIT] A Python-widget(pyQT)-based spectral fitting package, which provides a user-friendly display of EOVSA image cubes, spatially resolved spectra, and an interface to scipy-based fitting codes.
** [[Spectrogram Software]]
** [[Mapping Software]]
* <big>Data Analysis Guides</big>
** <big>[[EOVSA Data Analysis Tutorial 2022]]</big> and <big>[https://colab.research.google.com/drive/19NQb6Emb9HvKX4QHq9ZYCP3RM6nT7sDL#scrollTo=cLdDVptBGG-X EOVSA Workspace]</big> at [https://sphere.boulder.swri.edu/ SPHERE 2022 Workshop]
** <big>[https://colab.research.google.com/drive/1lSLLxgOG6b8kgu9Sk6kSKvrViyubnXG6?usp=sharing#scrollTo=xbXyyLmCFCGL EOVSA Data Analysis Tutorial at RHESSI 19 Workshop]</big>
** <big>[[EOVSA Data Analysis Tutorial]]</big> at [http://rhessi18.umn.edu/ RHESSI XVIII Workshop]
** [[Self-Calibrating Flare Data]] Example script and guides for self-calibrating EOVSA flare data (to be completed)


**[[IDB flare pipeline]] Tutorial to run the flare pipeline for quicklook images



* <big>EOVSA Modeling Guide</big>
**[[GX Simulator]]

* Other helpful links
** [https://casaguides.nrao.edu CASA Guides]
** [http://www.lmsal.com/solarsoft/ SolarSoft IDL]
** [http://www.atnf.csiro.au/computing/software/miriad/userguide/userhtml.html Miriad Guides]
** [https://sites.google.com/site/fgscodes/ Fast Gyrosynchrotron Codes (Alexey Kuznetsov's website)]
** [[Basic GitHub Tutorial]]


* <big>[[Full Disk Simulations]]</big>
* <big>[[All-Day Synthesis Issues]]</big>
* <big>[[Analyzing Pre-2017 Data]]</big>
* <big>[[Fixing Pipeline Problems pre-2021-Feb-07]]</big>

== EOVSA Documentation ==

* <big>General</big>
** [[Downconversion and Frequency Tuning]]
** [[Dealing with Radio Frequency Interference]]
** [[Switching between 200 MHz and 300 MHz Correlator]]
** [[Observing in "Fast" Mode]]

* <big>Computer-Network</big>
** [[Computing Systems]]
** [[Network]]

* <big>Control System</big>
** [[27-m Antenna Commands]]
** [[Schedule Commands]]
** [[Control Commands]]
** [[Attenuation and Level Control]]

* <big>Hardware</big>
** [[Hardware Overview]]
** [[2.1-m Antennas]]
** [[27-m Antennas]]

* <big>System Software</big>
** [[Calibration Database]]
** [[Stateframe Database]]
** [[Database Maintenance]]
** [[Create CASA measurement sets]]

* <big>Calibration</big>
**[[Calibration Overview]]
**[[Pointing Calibration]]
**[[Total Power Calibration]]
**[[System Gain Calibration]]
**[[Antenna Position]] (Baseline Calibration)
**[[Reference Gain Calibration]]
**[[Daily Gain Calibration]]
**[[Delay Calibration]]
**[[Bandpass Calibration]]
**[[Polarization Calibration]]
**[[Calibrator Survey]]
**[[Practical Calibration Tutorial]]

* <big>[[Starburst]]</big>

== System Software ==

* LabVIEW software
* Python code [https://github.com/dgary50/eovsa Github repository]
* [[Python3 Code Installation]]

== EOVSA Observing Log ==
[[2016 November]]; [[2016 December| December]]

[[2017 January]]; [[2017 February | February]]; [[2017 March | March]]; [[2017 April | April]]; [[2017 May | May]]; [[2017 June | June]];
[[2017 July | July]]; [[2017 August | August]]; [[2017 September | September]]; [[2017 October | October]]; [[2017 November | November]]; [[2017 December | December]]

[[2018 January]]; [[2018 February | February]]; [[2018 March | March]]; [[2018 April | April]]; [[2018 May | May]]; [[2018 June | June]];
[[2018 July | July]]; [[2018 August | August]]; [[2018 September | September]]; [[2018 October | October]]; [[2018 November | November]]; [[2018 December | December]]

[[2019 January]]; [[2019 February | February]]; [[2019 March | March]]; [[2019 April | April]]; [[2019 May | May]]; [[2019 June | June]];
[[2019 July | July]]; [[2019 August | August]]; [[2019 September | September]]; [[2019 October | October]]; [[2019 November | November]]; [[2019 December | December]]

[[2020 January]]; [[2020 February | February]]; [[2020 March | March]]; [[2020 April | April]]; [[2020 May | May]]; [[2020 June | June]];
[[2020 July | July]]; [[2020 August | August]]; [[2020 September | September]]; [[2020 October | October]]; [[2020 November | November]]; [[2020 December | December]]

[[2021 January]]; [[2021 February | February]]; [[2021 March | March]]; [[2021 April | April]]; [[2021 May | May]]; [[2021 June | June]];
[[2021 July | July]]; [[2021 August | August]]; [[2021 September | September]]; [[2021 October | October]]; [[2021 November | November]]; [[2021 December | December]]

[[2022 SQL Outage]]

[[2023 January]]; [[2023 February | February]]; [[2023 March | March]]; [[2023 April | April]]; [[2023 May | May]]; [[2023 June | June]];
[[2023 July | July]]; [[2023 August | August]]; [[2023 September | September]]; [[2023 October | October]]; [[2023 November | November]]; [[2023 December | December]]

[[2024 January]]; [[2024 February | February]]; [[2024 March | March]];[[2024 April | April]];[[2024 May |May]]; [[2024 June | June]]; [[2024 July | July]]; [[2024 August | August]];
[[2024 September | September]]

== SoD Observing Logs ==
* See [https://docs.google.com/document/d/1_iGnMRRrvb85Z0vT8-LzgQmCOKDSATEuQ0vTsn2C-dc/edit?usp=sharing SoD Routines] for detailed instructions for Scientist-on-Duty routines.
* 2024 [https://docs.google.com/document/d/1QDWw5y4HpcE7CSpzXwftMqQT4FDgNJj-6fRrgWrqdug/edit?usp=sharing May (and before that)], [https://docs.google.com/document/d/1Rh2gYBV2E454xVYEv8jx5IXKd1N2Z05ns4dhI2XCE08/edit?usp=sharing June], [https://docs.google.com/document/d/1beUpp6rgwjqSxKbuHzXIR9hhPrGyi0j-SjtEIeav9Vg/edit?usp=sharing July], [https://docs.google.com/document/d/1pSzUXW5gd-4cZAR-gglTUVM_J2UHMa4wYJ2AzD4cdEo/edit?usp=sharing August], [https://docs.google.com/document/d/18pArAP0kRDhXHbty_y3TtrygmWkC2oLn-UD7njIpRIo/edit?usp=sharing September], October, November, December

== Tohbans ==

[[Trouble Shooting Guide]]

[[Tohban Records]]

[[Owen's Notes]]

[[Caius' Notes]]

[[Tohban EOVSA Imaging Tutorial A-Z]]

[[Tohban OVRO-LWA Imaging Tutorial]]

[[Tohban Guide to Self Calibration and Imaging for EOVSA]]

[[Guide to Upgrade SolarSoft(SSW)]]

== EOVSA Publications ==
Here is a (partial) list of publications that utilize EOVSA data. See also the collection of EOVSA publications at [https://ui.adsabs.harvard.edu/public-libraries/eQ7HfPkySqydu-B8BCt6QQ this NASA/ADS Library].
; 2024
: Collier, H., Hayes, L. A., Yu, S., Battaglia, A. F., Ashfield, W., Polito, V., Harra, L. K., & Krucker, S. (2024), arXiv e-prints, arXiv:2402.10546. [https://ui.adsabs.harvard.edu/abs/2024arXiv240210546C “Localising pulsations in the hard X-ray and microwave emission of an X-class flare”]
: Saqri, J., Veronig, A. M., Battaglia, A. F., Dickson, E. C. M., Gary, D. E., & Krucker, S. (2024), Astronomy and Astrophysics, 683, A41. [https://ui.adsabs.harvard.edu/abs/2024A&A...683A..41S "Efficiency of solar microflares in accelerating electrons when rooted in a sunspot"]
; 2023
: Tan, B., Yan, Y., Huang, J., Zhang, Y., Tan, C., & Zhu, X. (2023), Advances in Space Research, 72, 5563. [https://ui.adsabs.harvard.edu/abs/2023AdSpR..72.5563T "The physics of solar spectral imaging observations in dm-cm wavelengths and the application on space weather"]

: Li, D., Li, Z., Shi, F., Su, Y., Chen, W., Yu, F., Li, C., Qiu, Y., Huang, Y., & Ning, Z. (2023), Astronomy and Astrophysics, 680, L15. [https://ui.adsabs.harvard.edu/abs/2023A&A...680L..15L "Observational signature of continuously operating drivers of decayless kink oscillation"]

: Wang, M., Chen, B., Yu, S., Gary, D. E., Lee, J., Wang, H., & Cohen, C. (2023), The Astrophysical Journal, 954, 32. [https://ui.adsabs.harvard.edu/abs/2023ApJ...954...32W "The Solar Origin of an In Situ Type III Radio Burst Event"]

: Gary, D. E. (2023), Annual Review of Astronomy and Astrophysics, 61, 427. [https://ui.adsabs.harvard.edu/abs/2023ARA&A..61..427G "New Insights from Imaging Spectroscopy of Solar Radio Emission"]

: Nita, G. M., Fleishman, G. D., Kuznetsov, A. A., Anfinogentov, S. A., Stupishin, A. G., Kontar, E. P., Schonfeld, S. J., Klimchuk, J. A., & Gary, D. E. (2023), The Astrophysical Journal Supplement Series, 267, 6. [https://ui.adsabs.harvard.edu/abs/2023ApJS..267....6N "Data-constrained Solar Modeling with GX Simulator"]

: Song, D.-C., Tian, J., Li, Y., Ding, M. D., Su, Y., Yu, S., Hong, J., Qiu, Y., Rao, S., Liu, X., Li, Q., Chen, X., Li, C., & Fang, C. (2023), The Astrophysical Journal, 952, L6. [https://ui.adsabs.harvard.edu/abs/2023ApJ...952L...6S "Spectral Observations and Modeling of a Solar White-light Flare Observed by CHASE"]

: Mondal, S., Chen, B., & Yu, S. (2023), The Astrophysical Journal, 949, 56. [https://ui.adsabs.harvard.edu/abs/2023ApJ...949...56M "Multifrequency Microwave Imaging of Weak Transients from the Quiet Solar Corona"]

: Kontar, E. P., Emslie, A. G., Motorina, G. G., & Dennis, B. R. (2023), The Astrophysical Journal, 947, L13. [https://ui.adsabs.harvard.edu/abs/2023ApJ...947L..13K "The Efficiency of Electron Acceleration during the Impulsive Phase of a Solar Flare"]

: Saqri, J., Veronig, A. M., Dickson, E. C. M., Podladchikova, T., Warmuth, A., Xiao, H., Gary, D. E., Battaglia, A. F., & Krucker, S. (2023), Astronomy and Astrophysics, 672, A23. [https://ui.adsabs.harvard.edu/abs/2023A&A...672A..23S "Multi-point study of the energy release and impulsive CME dynamics in an eruptive C7 flare"]
; 2022

: Kou, Y., Cheng, X., Wang, Y., Yu, S., Chen, B., Kontar, E. P., & Ding, M. (2022), Nature Communications, 13, 7680. [https://ui.adsabs.harvard.edu/abs/2022NatCo..13.7680K "Microwave imaging of quasi-periodic pulsations at flare current sheet"]

: Chertok, I. M. (2022), Monthly Notices of the Royal Astronomical Society, 517, 2709. [https://ui.adsabs.harvard.edu/abs/2022MNRAS.517.2709C "On some features of the solar proton event on 2021 October 28 - GLE73"]

: Lörinčík, J., Polito, V., De Pontieu, B., Yu, S., & Freij, N. (2022), Frontiers in Astronomy and Space Sciences, 9, 334. [https://ui.adsabs.harvard.edu/abs/2022FrASS...940945L "Rapid variations of Si IV spectra in a flare observed by interface region imaging spectrograph at a sub-second cadence"]

: Klein, K.-L., Musset, S., Vilmer, N., Briand, C., Krucker, S., Francesco Battaglia, A., Dresing, N., Palmroos, C., & Gary, D. E. (2022), Astronomy and Astrophysics, 663, A173. [https://ui.adsabs.harvard.edu/abs/2022A&A...663A.173K "The relativistic solar particle event on 28 October 2021: Evidence of particle acceleration within and escape from the solar corona"]

: Fleishman, G. D., Nita, G. M., Chen, B., Yu, S., & Gary, D. E. (2022), Nature, 606, 674. [https://ui.adsabs.harvard.edu/abs/2022Natur.606..674F "Solar flare accelerates nearly all electrons in a large coronal volume"]

: Li, X., Guo, F., Chen, B., Shen, C., & Glesener, L. (2022), The Astrophysical Journal, 932, 92. [https://ui.adsabs.harvard.edu/abs/2022ApJ...932...92L "Modeling Electron Acceleration and Transport in the Early Impulsive Phase of the 2017 September 10th Solar Flare"]

: Zhang, J., Chen, B., Yu, S., Tian, H., Wei, Y., Chen, H., Tan, G., Luo, Y., & Chen, X. (2022), The Astrophysical Journal, 932, 53. [https://ui.adsabs.harvard.edu/abs/2022ApJ...932...53Z "Implications for Additional Plasma Heating Driving the Extreme-ultraviolet Late Phase of a Solar Flare with Microwave Imaging Spectroscopy"]

: Liu, N., Jing, J., Xu, Y., & Wang, H. (2022), The Astrophysical Journal, 930, 154. [https://ui.adsabs.harvard.edu/abs/2022ApJ...930..154L "Multi-instrument Comparative Study of Temperature, Number Density, and Emission Measure during the Precursor Phase of a Solar Flare"]

: López, F. M., Giménez de Castro, C. G., Mandrini, C. H., Simões, P. J. A., Cristiani, G. D., Gary, D. E., Francile, C., & Démoulin, P. (2022), Astronomy and Astrophysics, 657, A51. [https://ui.adsabs.harvard.edu/abs/2022A&A...657A..51L "A solar flare driven by thermal conduction observed in mid-infrared"]

: Unverferth, J., & Longcope, D. (2021), The Astrophysical Journal, 923, 248. [https://ui.adsabs.harvard.edu/abs/2021ApJ...923..248U "Examining Flux Tube Interactions as a Cause of Sub-alfvénic Outflow"]
;2021

: Wei, Y., Chen, B., Yu, S., Wang, H., Jing, J., & Gary, D. E. (2021), The Astrophysical Journal, 923, 213. [https://ui.adsabs.harvard.edu/abs/2021ApJ...923..213W "Coronal Magnetic Field Measurements along a Partially Erupting Filament in a Solar Flare"]

: Jing, J., Inoue, S., Lee, J., Li, Q., Nita, G. M., Xu, Y., Liu, C., Gary, D. E., & Wang, H. (2021), The Astrophysical Journal, 922, 108. [https://ui.adsabs.harvard.edu/abs/2021ApJ...922..108J "Understanding the Initiation of the M2.4 Flare on 2017 July 14"]

: Battaglia, A. F., Saqri, J., Massa, P., Perracchione, E., Dickson, E. C. M., Xiao, H., Veronig, A. M., Warmuth, A., Battaglia, M., Hurford, G. J., Meuris, A., Limousin, O., Etesi, L., Maloney, S. A., Schwartz, R. A., Kuhar, M., Schuller, F., Senthamizh Pavai, V., Musset, S., Ryan, D. F., Kleint, L., Piana, M., Massone, A. M., Benvenuto, F., Sylwester, J., Litwicka, M., Stȩślicki, M., Mrozek, T., Vilmer, N., Fárník, F., Kašparová, J., Mann, G., Gallagher, P. T., Dennis, B. R., Csillaghy, A., Benz, A. O., & Krucker, S. (2021), Astronomy and Astrophysics, 656, A4. [https://ui.adsabs.harvard.edu/abs/2021A&A...656A...4B "STIX X-ray microflare observations during the Solar Orbiter commissioning phase"]

: Shaik, S. B., & Gary, D. E. (2021), The Astrophysical Journal, 919, 44. [https://ui.adsabs.harvard.edu/abs/2021ApJ...919...44S "Implications of Flat Optically Thick Microwave Spectra in Solar Flares for Source Size and Morphology"]

: Kocharov, L., Omodei, N., Mishev, A., Pesce-Rollins, M., Longo, F., Yu, S., Gary, D. E., Vainio, R., & Usoskin, I. (2021), The Astrophysical Journal, 915, 12. [https://ui.adsabs.harvard.edu/abs/2021ApJ...915...12K "Multiple Sources of Solar High-energy Protons"]

: Chen, B., Battaglia, M., Krucker, S., Reeves, K. K., & Glesener, L. (2021), The Astrophysical Journal, 908, L55. [https://ui.adsabs.harvard.edu/abs/2021ApJ...908L..55C "Energetic Electron Distribution of the Coronal Acceleration Region: First Results from Joint Microwave and Hard X-Ray Imaging Spectroscopy"]

: Chhabra, S., Gary, D. E., Hallinan, G., Anderson, M. M., Chen, B., Greenhill, L. J., & Price, D. C. (2021), The Astrophysical Journal, 906, 132. [https://ui.adsabs.harvard.edu/abs/2021ApJ...906..132C "Imaging Spectroscopy of CME-associated Solar Radio Bursts using OVRO-LWA"]
;2020 and earlier

: Reeves, K. K., Polito, V., Chen, B., Galan, G., Yu, S., Liu, W., & Li, G. (2020), The Astrophysical Journal, 905, 165. [https://ui.adsabs.harvard.edu/abs/2020ApJ...905..165R "Hot Plasma Flows and Oscillations in the Loop-top Region During the 2017 September 10 X8.2 Solar Flare"]

: Nindos, A. (2020), Frontiers in Astronomy and Space Sciences, 7, 57. [https://ui.adsabs.harvard.edu/abs/2020FrASS...7...57N "Incoherent Solar Radio Emission"]

: Yu, S., Chen, B., Reeves, K. K., Gary, D. E., Musset, S., Fleishman, G. D., Nita, G. M., & Glesener, L. (2020), The Astrophysical Journal, 900, 17. [https://ui.adsabs.harvard.edu/abs/2020ApJ...900...17Y "Magnetic Reconnection during the Post-impulsive Phase of a Long-duration Solar Flare: Bidirectional Outflows as a Cause of Microwave and X-Ray Bursts"]

: Chen, B., Yu, S., Reeves, K. K., & Gary, D. E. (2020), The Astrophysical Journal, 895, L50. [https://ui.adsabs.harvard.edu/abs/2020ApJ...895L..50C "Microwave Spectral Imaging of an Erupting Magnetic Flux Rope: Implications for the Standard Solar Flare Model in Three Dimensions"]

: Kuroda, N., Fleishman, G. D., Gary, D. E., Nita, G. M., Chen, B., & Yu, S. (2020), Frontiers in Astronomy and Space Sciences, 7, 22. [https://ui.adsabs.harvard.edu/abs/2020FrASS...7...22K "Evolution of Flare-accelerated Electrons Quantified by Spatially Resolved Analysis"]

: Glesener, L., Krucker, S., Duncan, J., Hannah, I. G., Grefenstette, B. W., Chen, B., Smith, D. M., White, S. M., & Hudson, H. (2020), The Astrophysical Journal, 891, L34. [https://ui.adsabs.harvard.edu/abs/2020ApJ...891L..34G "Accelerated Electrons Observed Down to <7 keV in a NuSTAR Solar Microflare"]

: Karlický, M., Chen, B., Gary, D. E., Kašparová, J., & Rybák, J. (2020), The Astrophysical Journal, 889, 72. [https://ui.adsabs.harvard.edu/abs/2020ApJ...889...72K "Drifting Pulsation Structure at the Very Beginning of the 2017 September 10 Limb Flare"]

: Fleishman, G. D., Gary, D. E., Chen, B., Kuroda, N., Yu, S., & Nita, G. M. (2020), Science, 367, 278. [https://ui.adsabs.harvard.edu/abs/2020Sci...367..278F "Decay of the coronal magnetic field can release sufficient energy to power a solar flare"]

: Chen, B., Shen, C., Gary, D. E., Reeves, K. K., Fleishman, G. D., Yu, S., Guo, F., Krucker, S., Lin, J., Nita, G. M., & Kong, X. (2020), Nature Astronomy, 4, 1140. [https://ui.adsabs.harvard.edu/abs/2020NatAs...4.1140C "Measurement of magnetic field and relativistic electrons along a solar flare current sheet"]

: Lee, J. (2018), Journal of Astronomy and Space Sciences, 35, 211. [https://ui.adsabs.harvard.edu/abs/2018JASS...35..211L "Analysis of Solar Microwave Burst Spectrum, I. Nonuniform Magnetic Field"]

: Gary, D. E., Bastian, T. S., Chen, B., Fleishman, G. D., & Glesener, L. (2018), Science with a Next Generation Very Large Array, 517, 99. [https://ui.adsabs.harvard.edu/abs/2018ASPC..517...99G "Radio Observations of Solar Flares"]

: Polito, V., Dudík, J., Kašparová, J., Dzifčáková, E., Reeves, K. K., Testa, P., & Chen, B. (2018), The Astrophysical Journal, 864, 63. [https://ui.adsabs.harvard.edu/abs/2018ApJ...864...63P "Broad Non-Gaussian Fe XXIV Line Profiles in the Impulsive Phase of the 2017 September 10 X8.3-class Flare Observed by Hinode/EIS"]

: Gary, D. E., Chen, B., Dennis, B. R., Fleishman, G. D., Hurford, G. J., Krucker, S., McTiernan, J. M., Nita, G. M., Shih, A. Y., White, S. M., & Yu, S. (2018), The Astrophysical Journal, 863, 83. [https://ui.adsabs.harvard.edu/abs/2018ApJ...863...83G "Microwave and Hard X-Ray Observations of the 2017 September 10 Solar Limb Flare"]

: Fleishman, G. D., Nita, G. M., Kuroda, N., Jia, S., Tong, K., Wen, R. R., & Zhizhuo, Z. (2018), The Astrophysical Journal, 859, 17. [https://ui.adsabs.harvard.edu/abs/2018ApJ...859...17F "Revealing the Evolution of Non-thermal Electrons in Solar Flares Using 3D Modeling"]

: Kuroda, N., Gary, D. E., Wang, H., Fleishman, G. D., Nita, G. M., & Jing, J. (2018), The Astrophysical Journal, 852, 32. [https://ui.adsabs.harvard.edu/abs/2018ApJ...852...32K "Three-dimensional Forward-fit Modeling of the Hard X-Ray and Microwave Emissions of the 2015 June 22 M6.5 Flare"]

: Wang, H., Liu, C., Ahn, K., Xu, Y., Jing, J., Deng, N., Huang, N., Liu, R., Kusano, K., Fleishman, G. D., Gary, D. E., & Cao, W. (2017), Nature Astronomy, 1, 0085. [https://ui.adsabs.harvard.edu/abs/2017NatAs...1E..85W "High-resolution observations of flare precursors in the low solar atmosphere"]

: Nita, G. M., Hickish, J., MacMahon, D., & Gary, D. E. (2016), Journal of Astronomical Instrumentation, 5, 1641009-7366. [https://ui.adsabs.harvard.edu/abs/2016JAI.....541009N "EOVSA Implementation of a Spectral Kurtosis Correlator for Transient Detection and Classification"]

: Nita, G. M., & Gary, D. E. (2016), Journal of Geophysical Research (Space Physics), 121, 7353. [https://ui.adsabs.harvard.edu/abs/2016JGRA..121.7353N "Measurement of duration and signal-to-noise ratio of astronomical transients using a Spectral Kurtosis spectrometer"]

: Wang, Z., Gary, D. E., Fleishman, G. D., & White, S. M. (2015), The Astrophysical Journal, 805, 93. [https://ui.adsabs.harvard.edu/abs/2015ApJ...805...93W "Coronal Magnetography of a Simulated Solar Active Region from Microwave Imaging Spectropolarimetry"]

: Gary, D. E., Fleishman, G. D., & Nita, G. M. (2013), Solar Physics, 288, 549. [https://ui.adsabs.harvard.edu/abs/2013SoPh..288..549G "Magnetography of Solar Flaring Loops with Microwave Imaging Spectropolarimetry"]

== VLA Flare List and Publications ==
See [http://www.ovsa.njit.edu/wiki/index.php/VLA_Data_Survey#List_of_Jansky_VLA_Solar_Observations this link] for a list of flare observations made by the [https://science.nrao.edu/facilities/vla/ Karl G. Jansky Very Large Array] (VLA). Below is a partial list of publications that utilize VLA solar data (see also [https://ui.adsabs.harvard.edu/public-libraries/ZwbjpLo9RS-viufWEoQ95Q this NASA/ADS Library]).
* [https://ui.adsabs.harvard.edu/abs/2022ApJ...940..137L/abstract Luo et al. (2022), ApJ, 940, 137] ''Multiple Regions of Nonthermal Quasiperiodic Pulsations during the Impulsive Phase of a Solar Flare''
* [https://ui.adsabs.harvard.edu/abs/2021ApJ...922..134B/abstract Battaglia et al. (2021), ApJ, 922, 134] ''Multiple Electron Acceleration Instances during a Series of Solar Microflares Observed Simultaneously at X-Rays and Microwaves''
* [https://ui.adsabs.harvard.edu/abs/2021ApJ...911....4L/abstract Luo et al. (2021), ApJ, 911, 4] ''Radio Spectral Imaging of an M8.4 Eruptive Solar Flare: Possible Evidence of a Termination Shock''
* [https://ui.adsabs.harvard.edu/abs/2021ApJ...910...40Z/abstract Zhang et al. (2021), ApJ, 910, 40] ''Multiwavelength Observations of the Formation and Eruption of a Complex Filament''
* [https://ui.adsabs.harvard.edu/abs/2020ApJ...904...94S/abstract Sharma et al. (2020), ApJ, 904, 94] ''Radio and X-Ray Observations of Short-lived Episodes of Electron Acceleration in a Solar Microflare''
* [https://ui.adsabs.harvard.edu/abs/2019ApJ...884...63C/abstract Chen et al. (2019), ApJ, 884, 63] ''Radio Spectroscopic Imaging of a Solar Flare Termination Shock: Split-band Feature as Evidence for Shock Compression''
* [https://ui.adsabs.harvard.edu/abs/2019ApJ...872...71Y/abstract Yu & Chen (2019), ApJ, 872, 71] ''Possible Detection of Subsecond-period Propagating Magnetohydrodynamics Waves in Post-reconnection Magnetic Loops during a Two-ribbon Solar Flare''
* [https://ui.adsabs.harvard.edu/abs/2018ApJ...866...62C/abstract Chen et al. (2018), ApJ, 866, 62] ''Magnetic Reconnection Null Points as the Origin of Semirelativistic Electron Beams in a Solar Jet
''
* [https://ui.adsabs.harvard.edu/abs/2017ApJ...848...77W/abstract Wang et al. (2016), ApJ, 848, 77] ''Dynamic Spectral Imaging of Decimetric Fiber Bursts in an Eruptive Solar Flare''
* [https://ui.adsabs.harvard.edu/abs/2015Sci...350.1238C/abstract Chen et al. (2015), Science, 350, 1238] ''Particle acceleration by a solar flare termination shock''
* [https://ui.adsabs.harvard.edu/abs/2014ApJ...794..149C/abstract Chen et al. (2014), ApJ, 794, 149] ''Direct Evidence of an Eruptive, Filament-hosting Magnetic Flux Rope Leading to a Fast Solar Coronal Mass Ejection''
* [https://ui.adsabs.harvard.edu/abs/2013ApJ...763L..21C/abstract Chen et al. (2013), ApJL, 763, 21] ''Tracing Electron Beams in the Sun's Corona with Radio Dynamic Imaging Spectroscopy''

==Radio Data from Around The Heliosphere==
* [http://ovsa.njit.edu//wiki/index.php/Radio_Data_from_Around_the_World#Radio_Data_Access '' Radio Data '']

=OVRO-LWA Solar-Dedicated Spectroscopic Imager=
The OVRO-LWA (Owens Valley Radio Observatory Long Wavelength Array) has recently been upgraded to include a solar-dedicated beam and two solar imaging modes (slow visibilities of 352 antennas with a 10-s cadence, and fast visibilities of 48 antennas with a 0.1-s cadence). The large collecting area and excellent calibration provide unprecedented high-sensitivity imaging of the quiet Sun and bursts. The array is currently in commissioning and observations are not yet continuous, but they are becoming more so. See the daily realtime data at http://ovsa.njit.edu/status.php for '''real-time display of the spectrogram and a selection of images''', both updated on a 1-min cadence.

==Solar-Dedicated Modes==
===Beamformer===
The beamformer uses the 256 core antennas to form a synthesized beam of more than 1 degree in size that tracks the Sun from sunrise to sunset. This permits a continuous record of the full-Stokes total flux (without spatial resolution) of the Sun (a dynamic spectrum) with 24 kHz frequency resolution (3072 frequencies from 15-90 MHz) and as low as 1 ms time resolution.

===Slow Visibility Imaging===
In this mode, the entire 352-element array is interferometrically correlated to provide visibilities for imaging at all 3072 frequencies at 10-s time resolution. This is ideal for imaging quiet Sun and slowly-varying emission such as coronal mass ejections and active region variability.

===Fast Visibility Imaging===
In this mode, a subset of 48 antennas (chosen to include mainly outer antennas to maintain good spatial resolution) is interferometrically correlated to provide visibilities for imaging at 768 frequencies (96 kHz frequency resolution) at 0.1-s time resolution. This is ideal for imaging rapidly varying emission such as type II and type III bursts as well as many other solar spectral fine structures.

==Inital Data Access==
In its current commissioning state, we try to run the beamformer and imaging pipeline every day in real-time since November 2023 (no latency for beamforming spectrograms and 5-10 min latency for images). Quicklook real-time spectrograms/images can be accessed from http://ovsa.njit.edu/status.php. To access data from previous days, use the following links (replace yyyymmdd with the date you desire):
* Quicklook beamformer total-power spectrograms: http://ovsa.njit.edu/lwa-data/1min_spectra/yyyymmdd/. Check this link for additional daily plots [[Daily OVRO-LWA Beamformer Data]].
* Quicklook multi-frequency movies at 1-min cadence: http://ovsa.njit.edu/lwa-data/1min_images/yyyymmdd/movie_yyyy-mm-dd.html

Note our pipeline processing development is still in the early phase. For example, absolute flux calibrations have not been done for the beamformer spectrograms. Also, artificial effects (including ionospheric refraction effects) are present in the images that cause distortions/shifts. We caution interested users only to consider them for quick-look purposes at this point. Please contact the EOVSA PIs (Dale Gary, Bin Chen) if you intend to use them for science.

==Operation Notes==
===Starting solar beamforming observations===
* Log into lwacalim10 (this is the only node that allows submissions)
* Activate the deployment conda environment
<pre> conda activate deployment </pre>
* Check what schedules are there
<pre>
lwaobserving show-schedule
</pre>
* Submit the schedule for the next 7 days (note that sdf files are written to /tmp/solar_<date>_<time>.sdf and will be owned by you).
<pre>
ipython
cd /home/dgary
import make_solar_sdf
make_solar_sdf.multiday_obs(ndays=7)
</pre>
* Calibrate the beam
<pre>
cd /home/pipeline/proj/lwa-shell/mnc_python/
from mnc import control
con=control.Controller('/opt/devel/dgary/lwa_config_calim_std.yaml')
con.configure_xengine(['dr2'], calibratebeams=True)
</pre>

Owens Valley Solar Arrays

2024-09-26T22:38:50Z

Binchen: /* OVRO-LWA Solar-Dedicated Spectroscopic Imager */

[[File:Eovsa1.png|border|text-top|800px]]

<big>[http://ovsa.njit.edu/ EOVSA] (Expanded Owens Valley Solar Array) is a solar-dedicated radio interferometer operated by the New Jersey Institute of Technology and serving as a '''National Science Foundation Geospace Facility'''. [[File:NSF.jpg|70px]]
<pre>Operation of EOVSA is supported by the National Science Foundation under Grant No. AGS-2130832. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. </pre>
This wiki serves as the site for EOVSA documentation. </big>

[[File:OVRO-LWA1.png|border|text-top|800px]]

<big>OVRO-LWA (Owens Valley Radio Observatory Long Wavelength Array) is an all-sky imager that has a new solar-dedicated spectroscopic imaging mode. OVRO-LWA is a multi-institutional collaboration led by Caltech. NJIT Solar Radio Group is leading its solar-mode development and science. At the bottom of this page are new links for that facility. </big>

== EOVSA Flare List ==

* [https://ovsa.njit.edu/flarelist Query EOVSA Flare list]
* List of EOVSA flares in separate years: [[2024]], [[2023]], [[2022]], [[2021]], [[2020]], [[2019]], [[2017]]

== Using EOVSA Data ==
* <big>[[EOVSA Data products]]</big>: An introduction to standard EOVSA spectrogram and spectral image products with example scripts for reading and plotting.
* <big>[[EOVSA Data Policy]]</big>: Policy for using EOVSA data products.
* <big>Analysis Software</big>: These are for in-depth use of EOVSA data (from calibrated visibilities) and tools for quantitative analysis.
** [https://github.com/suncasa/suncasa SunCASA] A wrapper around [https://casa.nrao.edu/ CASA (the Common Astronomy Software Applications package)] for synthesis imaging and visualizing solar spectral imaging data. CASA is one of the leading software tool for "supporting the data post-processing needs of the next generation of radio astronomical telescopes such as ALMA and VLA", an international effort led by the [https://public.nrao.edu/ National Radio Astronomy Observatory]. The current version of CASA uses Python (2.7) interface. More information about CASA can be found on [https://casa.nrao.edu/ NRAO's CASA website ]. Note, CASA is available ONLY on UNIX-BASED PLATFORMS (and therefore, so is SunCASA).
** [https://github.com/Gelu-Nita/GSFIT GSFIT] A IDL-widget(GUI)-based spectral fitting package called gsfit, which provides a user-friendly display of EOVSA image cubes and an interface to fast fitting codes (via platform-dependent shared-object libraries).
** [https://github.com/suncasa/pygsfit pyGSFIT] A Python-widget(pyQT)-based spectral fitting package, which provides a user-friendly display of EOVSA image cubes, spatially resolved spectra, and an interface to scipy-based fitting codes.
** [[Spectrogram Software]]
** [[Mapping Software]]
* <big>Data Analysis Guides</big>
** <big>[[EOVSA Data Analysis Tutorial 2022]]</big> and <big>[https://colab.research.google.com/drive/19NQb6Emb9HvKX4QHq9ZYCP3RM6nT7sDL#scrollTo=cLdDVptBGG-X EOVSA Workspace]</big> at [https://sphere.boulder.swri.edu/ SPHERE 2022 Workshop]
** <big>[https://colab.research.google.com/drive/1lSLLxgOG6b8kgu9Sk6kSKvrViyubnXG6?usp=sharing#scrollTo=xbXyyLmCFCGL EOVSA Data Analysis Tutorial at RHESSI 19 Workshop]</big>
** <big>[[EOVSA Data Analysis Tutorial]]</big> at [http://rhessi18.umn.edu/ RHESSI XVIII Workshop]
** [[Self-Calibrating Flare Data]] Example script and guides for self-calibrating EOVSA flare data (to be completed)


**[[IDB flare pipeline]] Tutorial to run the flare pipeline for quicklook images



* <big>EOVSA Modeling Guide</big>
**[[GX Simulator]]

* Other helpful links
** [https://casaguides.nrao.edu CASA Guides]
** [http://www.lmsal.com/solarsoft/ SolarSoft IDL]
** [http://www.atnf.csiro.au/computing/software/miriad/userguide/userhtml.html Miriad Guides]
** [https://sites.google.com/site/fgscodes/ Fast Gyrosynchrotron Codes (Alexey Kuznetsov's website)]
** [[Basic GitHub Tutorial]]


* <big>[[Full Disk Simulations]]</big>
* <big>[[All-Day Synthesis Issues]]</big>
* <big>[[Analyzing Pre-2017 Data]]</big>
* <big>[[Fixing Pipeline Problems pre-2021-Feb-07]]</big>

== EOVSA Documentation ==

* <big>General</big>
** [[Downconversion and Frequency Tuning]]
** [[Dealing with Radio Frequency Interference]]
** [[Switching between 200 MHz and 300 MHz Correlator]]
** [[Observing in "Fast" Mode]]

* <big>Computer-Network</big>
** [[Computing Systems]]
** [[Network]]

* <big>Control System</big>
** [[27-m Antenna Commands]]
** [[Schedule Commands]]
** [[Control Commands]]
** [[Attenuation and Level Control]]

* <big>Hardware</big>
** [[Hardware Overview]]
** [[2.1-m Antennas]]
** [[27-m Antennas]]

* <big>System Software</big>
** [[Calibration Database]]
** [[Stateframe Database]]
** [[Database Maintenance]]
** [[Create CASA measurement sets]]

* <big>Calibration</big>
**[[Calibration Overview]]
**[[Pointing Calibration]]
**[[Total Power Calibration]]
**[[System Gain Calibration]]
**[[Antenna Position]] (Baseline Calibration)
**[[Reference Gain Calibration]]
**[[Daily Gain Calibration]]
**[[Delay Calibration]]
**[[Bandpass Calibration]]
**[[Polarization Calibration]]
**[[Calibrator Survey]]
**[[Practical Calibration Tutorial]]

* <big>[[Starburst]]</big>

== System Software ==

* LabVIEW software
* Python code [https://github.com/dgary50/eovsa Github repository]
* [[Python3 Code Installation]]

== EOVSA Observing Log ==
[[2016 November]]; [[2016 December| December]]

[[2017 January]]; [[2017 February | February]]; [[2017 March | March]]; [[2017 April | April]]; [[2017 May | May]]; [[2017 June | June]];
[[2017 July | July]]; [[2017 August | August]]; [[2017 September | September]]; [[2017 October | October]]; [[2017 November | November]]; [[2017 December | December]]

[[2018 January]]; [[2018 February | February]]; [[2018 March | March]]; [[2018 April | April]]; [[2018 May | May]]; [[2018 June | June]];
[[2018 July | July]]; [[2018 August | August]]; [[2018 September | September]]; [[2018 October | October]]; [[2018 November | November]]; [[2018 December | December]]

[[2019 January]]; [[2019 February | February]]; [[2019 March | March]]; [[2019 April | April]]; [[2019 May | May]]; [[2019 June | June]];
[[2019 July | July]]; [[2019 August | August]]; [[2019 September | September]]; [[2019 October | October]]; [[2019 November | November]]; [[2019 December | December]]

[[2020 January]]; [[2020 February | February]]; [[2020 March | March]]; [[2020 April | April]]; [[2020 May | May]]; [[2020 June | June]];
[[2020 July | July]]; [[2020 August | August]]; [[2020 September | September]]; [[2020 October | October]]; [[2020 November | November]]; [[2020 December | December]]

[[2021 January]]; [[2021 February | February]]; [[2021 March | March]]; [[2021 April | April]]; [[2021 May | May]]; [[2021 June | June]];
[[2021 July | July]]; [[2021 August | August]]; [[2021 September | September]]; [[2021 October | October]]; [[2021 November | November]]; [[2021 December | December]]

[[2022 SQL Outage]]

[[2023 January]]; [[2023 February | February]]; [[2023 March | March]]; [[2023 April | April]]; [[2023 May | May]]; [[2023 June | June]];
[[2023 July | July]]; [[2023 August | August]]; [[2023 September | September]]; [[2023 October | October]]; [[2023 November | November]]; [[2023 December | December]]

[[2024 January]]; [[2024 February | February]]; [[2024 March | March]];[[2024 April | April]];[[2024 May |May]]; [[2024 June | June]]; [[2024 July | July]]; [[2024 August | August]];
[[2024 September | September]]

== SoD Observing Logs ==
* See [https://docs.google.com/document/d/1_iGnMRRrvb85Z0vT8-LzgQmCOKDSATEuQ0vTsn2C-dc/edit?usp=sharing SoD Routines] for detailed instructions for Scientist-on-Duty routines.
* 2024 [https://docs.google.com/document/d/1QDWw5y4HpcE7CSpzXwftMqQT4FDgNJj-6fRrgWrqdug/edit?usp=sharing May (and before that)], [https://docs.google.com/document/d/1Rh2gYBV2E454xVYEv8jx5IXKd1N2Z05ns4dhI2XCE08/edit?usp=sharing June], [https://docs.google.com/document/d/1beUpp6rgwjqSxKbuHzXIR9hhPrGyi0j-SjtEIeav9Vg/edit?usp=sharing July], [https://docs.google.com/document/d/1pSzUXW5gd-4cZAR-gglTUVM_J2UHMa4wYJ2AzD4cdEo/edit?usp=sharing August], [https://docs.google.com/document/d/18pArAP0kRDhXHbty_y3TtrygmWkC2oLn-UD7njIpRIo/edit?usp=sharing September], October, November, December

== Tohbans ==

[[Trouble Shooting Guide]]

[[Tohban Records]]

[[Owen's Notes]]

[[Caius' Notes]]

[[Tohban EOVSA Imaging Tutorial A-Z]]

[[Tohban OVRO-LWA Imaging Tutorial]]

[[Tohban Guide to Self Calibration and Imaging for EOVSA]]

[[Guide to Upgrade SolarSoft(SSW)]]

== EOVSA Publications ==
Here is a (partial) list of publications that utilize EOVSA data. See also the collection of EOVSA publications at [https://ui.adsabs.harvard.edu/public-libraries/eQ7HfPkySqydu-B8BCt6QQ this NASA/ADS Library].
; 2024
: Collier, H., Hayes, L. A., Yu, S., Battaglia, A. F., Ashfield, W., Polito, V., Harra, L. K., & Krucker, S. (2024), arXiv e-prints, arXiv:2402.10546. [https://ui.adsabs.harvard.edu/abs/2024arXiv240210546C “Localising pulsations in the hard X-ray and microwave emission of an X-class flare”]
: Saqri, J., Veronig, A. M., Battaglia, A. F., Dickson, E. C. M., Gary, D. E., & Krucker, S. (2024), Astronomy and Astrophysics, 683, A41. [https://ui.adsabs.harvard.edu/abs/2024A&A...683A..41S "Efficiency of solar microflares in accelerating electrons when rooted in a sunspot"]
; 2023
: Tan, B., Yan, Y., Huang, J., Zhang, Y., Tan, C., & Zhu, X. (2023), Advances in Space Research, 72, 5563. [https://ui.adsabs.harvard.edu/abs/2023AdSpR..72.5563T "The physics of solar spectral imaging observations in dm-cm wavelengths and the application on space weather"]

: Li, D., Li, Z., Shi, F., Su, Y., Chen, W., Yu, F., Li, C., Qiu, Y., Huang, Y., & Ning, Z. (2023), Astronomy and Astrophysics, 680, L15. [https://ui.adsabs.harvard.edu/abs/2023A&A...680L..15L "Observational signature of continuously operating drivers of decayless kink oscillation"]

: Wang, M., Chen, B., Yu, S., Gary, D. E., Lee, J., Wang, H., & Cohen, C. (2023), The Astrophysical Journal, 954, 32. [https://ui.adsabs.harvard.edu/abs/2023ApJ...954...32W "The Solar Origin of an In Situ Type III Radio Burst Event"]

: Gary, D. E. (2023), Annual Review of Astronomy and Astrophysics, 61, 427. [https://ui.adsabs.harvard.edu/abs/2023ARA&A..61..427G "New Insights from Imaging Spectroscopy of Solar Radio Emission"]

: Nita, G. M., Fleishman, G. D., Kuznetsov, A. A., Anfinogentov, S. A., Stupishin, A. G., Kontar, E. P., Schonfeld, S. J., Klimchuk, J. A., & Gary, D. E. (2023), The Astrophysical Journal Supplement Series, 267, 6. [https://ui.adsabs.harvard.edu/abs/2023ApJS..267....6N "Data-constrained Solar Modeling with GX Simulator"]

: Song, D.-C., Tian, J., Li, Y., Ding, M. D., Su, Y., Yu, S., Hong, J., Qiu, Y., Rao, S., Liu, X., Li, Q., Chen, X., Li, C., & Fang, C. (2023), The Astrophysical Journal, 952, L6. [https://ui.adsabs.harvard.edu/abs/2023ApJ...952L...6S "Spectral Observations and Modeling of a Solar White-light Flare Observed by CHASE"]

: Mondal, S., Chen, B., & Yu, S. (2023), The Astrophysical Journal, 949, 56. [https://ui.adsabs.harvard.edu/abs/2023ApJ...949...56M "Multifrequency Microwave Imaging of Weak Transients from the Quiet Solar Corona"]

: Kontar, E. P., Emslie, A. G., Motorina, G. G., & Dennis, B. R. (2023), The Astrophysical Journal, 947, L13. [https://ui.adsabs.harvard.edu/abs/2023ApJ...947L..13K "The Efficiency of Electron Acceleration during the Impulsive Phase of a Solar Flare"]

: Saqri, J., Veronig, A. M., Dickson, E. C. M., Podladchikova, T., Warmuth, A., Xiao, H., Gary, D. E., Battaglia, A. F., & Krucker, S. (2023), Astronomy and Astrophysics, 672, A23. [https://ui.adsabs.harvard.edu/abs/2023A&A...672A..23S "Multi-point study of the energy release and impulsive CME dynamics in an eruptive C7 flare"]
; 2022

: Kou, Y., Cheng, X., Wang, Y., Yu, S., Chen, B., Kontar, E. P., & Ding, M. (2022), Nature Communications, 13, 7680. [https://ui.adsabs.harvard.edu/abs/2022NatCo..13.7680K "Microwave imaging of quasi-periodic pulsations at flare current sheet"]

: Chertok, I. M. (2022), Monthly Notices of the Royal Astronomical Society, 517, 2709. [https://ui.adsabs.harvard.edu/abs/2022MNRAS.517.2709C "On some features of the solar proton event on 2021 October 28 - GLE73"]

: Lörinčík, J., Polito, V., De Pontieu, B., Yu, S., & Freij, N. (2022), Frontiers in Astronomy and Space Sciences, 9, 334. [https://ui.adsabs.harvard.edu/abs/2022FrASS...940945L "Rapid variations of Si IV spectra in a flare observed by interface region imaging spectrograph at a sub-second cadence"]

: Klein, K.-L., Musset, S., Vilmer, N., Briand, C., Krucker, S., Francesco Battaglia, A., Dresing, N., Palmroos, C., & Gary, D. E. (2022), Astronomy and Astrophysics, 663, A173. [https://ui.adsabs.harvard.edu/abs/2022A&A...663A.173K "The relativistic solar particle event on 28 October 2021: Evidence of particle acceleration within and escape from the solar corona"]

: Fleishman, G. D., Nita, G. M., Chen, B., Yu, S., & Gary, D. E. (2022), Nature, 606, 674. [https://ui.adsabs.harvard.edu/abs/2022Natur.606..674F "Solar flare accelerates nearly all electrons in a large coronal volume"]

: Li, X., Guo, F., Chen, B., Shen, C., & Glesener, L. (2022), The Astrophysical Journal, 932, 92. [https://ui.adsabs.harvard.edu/abs/2022ApJ...932...92L "Modeling Electron Acceleration and Transport in the Early Impulsive Phase of the 2017 September 10th Solar Flare"]

: Zhang, J., Chen, B., Yu, S., Tian, H., Wei, Y., Chen, H., Tan, G., Luo, Y., & Chen, X. (2022), The Astrophysical Journal, 932, 53. [https://ui.adsabs.harvard.edu/abs/2022ApJ...932...53Z "Implications for Additional Plasma Heating Driving the Extreme-ultraviolet Late Phase of a Solar Flare with Microwave Imaging Spectroscopy"]

: Liu, N., Jing, J., Xu, Y., & Wang, H. (2022), The Astrophysical Journal, 930, 154. [https://ui.adsabs.harvard.edu/abs/2022ApJ...930..154L "Multi-instrument Comparative Study of Temperature, Number Density, and Emission Measure during the Precursor Phase of a Solar Flare"]

: López, F. M., Giménez de Castro, C. G., Mandrini, C. H., Simões, P. J. A., Cristiani, G. D., Gary, D. E., Francile, C., & Démoulin, P. (2022), Astronomy and Astrophysics, 657, A51. [https://ui.adsabs.harvard.edu/abs/2022A&A...657A..51L "A solar flare driven by thermal conduction observed in mid-infrared"]

: Unverferth, J., & Longcope, D. (2021), The Astrophysical Journal, 923, 248. [https://ui.adsabs.harvard.edu/abs/2021ApJ...923..248U "Examining Flux Tube Interactions as a Cause of Sub-alfvénic Outflow"]
;2021

: Wei, Y., Chen, B., Yu, S., Wang, H., Jing, J., & Gary, D. E. (2021), The Astrophysical Journal, 923, 213. [https://ui.adsabs.harvard.edu/abs/2021ApJ...923..213W "Coronal Magnetic Field Measurements along a Partially Erupting Filament in a Solar Flare"]

: Jing, J., Inoue, S., Lee, J., Li, Q., Nita, G. M., Xu, Y., Liu, C., Gary, D. E., & Wang, H. (2021), The Astrophysical Journal, 922, 108. [https://ui.adsabs.harvard.edu/abs/2021ApJ...922..108J "Understanding the Initiation of the M2.4 Flare on 2017 July 14"]

: Battaglia, A. F., Saqri, J., Massa, P., Perracchione, E., Dickson, E. C. M., Xiao, H., Veronig, A. M., Warmuth, A., Battaglia, M., Hurford, G. J., Meuris, A., Limousin, O., Etesi, L., Maloney, S. A., Schwartz, R. A., Kuhar, M., Schuller, F., Senthamizh Pavai, V., Musset, S., Ryan, D. F., Kleint, L., Piana, M., Massone, A. M., Benvenuto, F., Sylwester, J., Litwicka, M., Stȩślicki, M., Mrozek, T., Vilmer, N., Fárník, F., Kašparová, J., Mann, G., Gallagher, P. T., Dennis, B. R., Csillaghy, A., Benz, A. O., & Krucker, S. (2021), Astronomy and Astrophysics, 656, A4. [https://ui.adsabs.harvard.edu/abs/2021A&A...656A...4B "STIX X-ray microflare observations during the Solar Orbiter commissioning phase"]

: Shaik, S. B., & Gary, D. E. (2021), The Astrophysical Journal, 919, 44. [https://ui.adsabs.harvard.edu/abs/2021ApJ...919...44S "Implications of Flat Optically Thick Microwave Spectra in Solar Flares for Source Size and Morphology"]

: Kocharov, L., Omodei, N., Mishev, A., Pesce-Rollins, M., Longo, F., Yu, S., Gary, D. E., Vainio, R., & Usoskin, I. (2021), The Astrophysical Journal, 915, 12. [https://ui.adsabs.harvard.edu/abs/2021ApJ...915...12K "Multiple Sources of Solar High-energy Protons"]

: Chen, B., Battaglia, M., Krucker, S., Reeves, K. K., & Glesener, L. (2021), The Astrophysical Journal, 908, L55. [https://ui.adsabs.harvard.edu/abs/2021ApJ...908L..55C "Energetic Electron Distribution of the Coronal Acceleration Region: First Results from Joint Microwave and Hard X-Ray Imaging Spectroscopy"]

: Chhabra, S., Gary, D. E., Hallinan, G., Anderson, M. M., Chen, B., Greenhill, L. J., & Price, D. C. (2021), The Astrophysical Journal, 906, 132. [https://ui.adsabs.harvard.edu/abs/2021ApJ...906..132C "Imaging Spectroscopy of CME-associated Solar Radio Bursts using OVRO-LWA"]
;2020 and earlier

: Reeves, K. K., Polito, V., Chen, B., Galan, G., Yu, S., Liu, W., & Li, G. (2020), The Astrophysical Journal, 905, 165. [https://ui.adsabs.harvard.edu/abs/2020ApJ...905..165R "Hot Plasma Flows and Oscillations in the Loop-top Region During the 2017 September 10 X8.2 Solar Flare"]

: Nindos, A. (2020), Frontiers in Astronomy and Space Sciences, 7, 57. [https://ui.adsabs.harvard.edu/abs/2020FrASS...7...57N "Incoherent Solar Radio Emission"]

: Yu, S., Chen, B., Reeves, K. K., Gary, D. E., Musset, S., Fleishman, G. D., Nita, G. M., & Glesener, L. (2020), The Astrophysical Journal, 900, 17. [https://ui.adsabs.harvard.edu/abs/2020ApJ...900...17Y "Magnetic Reconnection during the Post-impulsive Phase of a Long-duration Solar Flare: Bidirectional Outflows as a Cause of Microwave and X-Ray Bursts"]

: Chen, B., Yu, S., Reeves, K. K., & Gary, D. E. (2020), The Astrophysical Journal, 895, L50. [https://ui.adsabs.harvard.edu/abs/2020ApJ...895L..50C "Microwave Spectral Imaging of an Erupting Magnetic Flux Rope: Implications for the Standard Solar Flare Model in Three Dimensions"]

: Kuroda, N., Fleishman, G. D., Gary, D. E., Nita, G. M., Chen, B., & Yu, S. (2020), Frontiers in Astronomy and Space Sciences, 7, 22. [https://ui.adsabs.harvard.edu/abs/2020FrASS...7...22K "Evolution of Flare-accelerated Electrons Quantified by Spatially Resolved Analysis"]

: Glesener, L., Krucker, S., Duncan, J., Hannah, I. G., Grefenstette, B. W., Chen, B., Smith, D. M., White, S. M., & Hudson, H. (2020), The Astrophysical Journal, 891, L34. [https://ui.adsabs.harvard.edu/abs/2020ApJ...891L..34G "Accelerated Electrons Observed Down to <7 keV in a NuSTAR Solar Microflare"]

: Karlický, M., Chen, B., Gary, D. E., Kašparová, J., & Rybák, J. (2020), The Astrophysical Journal, 889, 72. [https://ui.adsabs.harvard.edu/abs/2020ApJ...889...72K "Drifting Pulsation Structure at the Very Beginning of the 2017 September 10 Limb Flare"]

: Fleishman, G. D., Gary, D. E., Chen, B., Kuroda, N., Yu, S., & Nita, G. M. (2020), Science, 367, 278. [https://ui.adsabs.harvard.edu/abs/2020Sci...367..278F "Decay of the coronal magnetic field can release sufficient energy to power a solar flare"]

: Chen, B., Shen, C., Gary, D. E., Reeves, K. K., Fleishman, G. D., Yu, S., Guo, F., Krucker, S., Lin, J., Nita, G. M., & Kong, X. (2020), Nature Astronomy, 4, 1140. [https://ui.adsabs.harvard.edu/abs/2020NatAs...4.1140C "Measurement of magnetic field and relativistic electrons along a solar flare current sheet"]

: Lee, J. (2018), Journal of Astronomy and Space Sciences, 35, 211. [https://ui.adsabs.harvard.edu/abs/2018JASS...35..211L "Analysis of Solar Microwave Burst Spectrum, I. Nonuniform Magnetic Field"]

: Gary, D. E., Bastian, T. S., Chen, B., Fleishman, G. D., & Glesener, L. (2018), Science with a Next Generation Very Large Array, 517, 99. [https://ui.adsabs.harvard.edu/abs/2018ASPC..517...99G "Radio Observations of Solar Flares"]

: Polito, V., Dudík, J., Kašparová, J., Dzifčáková, E., Reeves, K. K., Testa, P., & Chen, B. (2018), The Astrophysical Journal, 864, 63. [https://ui.adsabs.harvard.edu/abs/2018ApJ...864...63P "Broad Non-Gaussian Fe XXIV Line Profiles in the Impulsive Phase of the 2017 September 10 X8.3-class Flare Observed by Hinode/EIS"]

: Gary, D. E., Chen, B., Dennis, B. R., Fleishman, G. D., Hurford, G. J., Krucker, S., McTiernan, J. M., Nita, G. M., Shih, A. Y., White, S. M., & Yu, S. (2018), The Astrophysical Journal, 863, 83. [https://ui.adsabs.harvard.edu/abs/2018ApJ...863...83G "Microwave and Hard X-Ray Observations of the 2017 September 10 Solar Limb Flare"]

: Fleishman, G. D., Nita, G. M., Kuroda, N., Jia, S., Tong, K., Wen, R. R., & Zhizhuo, Z. (2018), The Astrophysical Journal, 859, 17. [https://ui.adsabs.harvard.edu/abs/2018ApJ...859...17F "Revealing the Evolution of Non-thermal Electrons in Solar Flares Using 3D Modeling"]

: Kuroda, N., Gary, D. E., Wang, H., Fleishman, G. D., Nita, G. M., & Jing, J. (2018), The Astrophysical Journal, 852, 32. [https://ui.adsabs.harvard.edu/abs/2018ApJ...852...32K "Three-dimensional Forward-fit Modeling of the Hard X-Ray and Microwave Emissions of the 2015 June 22 M6.5 Flare"]

: Wang, H., Liu, C., Ahn, K., Xu, Y., Jing, J., Deng, N., Huang, N., Liu, R., Kusano, K., Fleishman, G. D., Gary, D. E., & Cao, W. (2017), Nature Astronomy, 1, 0085. [https://ui.adsabs.harvard.edu/abs/2017NatAs...1E..85W "High-resolution observations of flare precursors in the low solar atmosphere"]

: Nita, G. M., Hickish, J., MacMahon, D., & Gary, D. E. (2016), Journal of Astronomical Instrumentation, 5, 1641009-7366. [https://ui.adsabs.harvard.edu/abs/2016JAI.....541009N "EOVSA Implementation of a Spectral Kurtosis Correlator for Transient Detection and Classification"]

: Nita, G. M., & Gary, D. E. (2016), Journal of Geophysical Research (Space Physics), 121, 7353. [https://ui.adsabs.harvard.edu/abs/2016JGRA..121.7353N "Measurement of duration and signal-to-noise ratio of astronomical transients using a Spectral Kurtosis spectrometer"]

: Wang, Z., Gary, D. E., Fleishman, G. D., & White, S. M. (2015), The Astrophysical Journal, 805, 93. [https://ui.adsabs.harvard.edu/abs/2015ApJ...805...93W "Coronal Magnetography of a Simulated Solar Active Region from Microwave Imaging Spectropolarimetry"]

: Gary, D. E., Fleishman, G. D., & Nita, G. M. (2013), Solar Physics, 288, 549. [https://ui.adsabs.harvard.edu/abs/2013SoPh..288..549G "Magnetography of Solar Flaring Loops with Microwave Imaging Spectropolarimetry"]

== VLA Flare List and Publications ==
See [http://www.ovsa.njit.edu/wiki/index.php/VLA_Data_Survey#List_of_Jansky_VLA_Solar_Observations this link] for a list of flare observations made by the [https://science.nrao.edu/facilities/vla/ Karl G. Jansky Very Large Array] (VLA). Below is a partial list of publications that utilize VLA solar data (see also [https://ui.adsabs.harvard.edu/public-libraries/ZwbjpLo9RS-viufWEoQ95Q this NASA/ADS Library]).
* [https://ui.adsabs.harvard.edu/abs/2022ApJ...940..137L/abstract Luo et al. (2022), ApJ, 940, 137] ''Multiple Regions of Nonthermal Quasiperiodic Pulsations during the Impulsive Phase of a Solar Flare''
* [https://ui.adsabs.harvard.edu/abs/2021ApJ...922..134B/abstract Battaglia et al. (2021), ApJ, 922, 134] ''Multiple Electron Acceleration Instances during a Series of Solar Microflares Observed Simultaneously at X-Rays and Microwaves''
* [https://ui.adsabs.harvard.edu/abs/2021ApJ...911....4L/abstract Luo et al. (2021), ApJ, 911, 4] ''Radio Spectral Imaging of an M8.4 Eruptive Solar Flare: Possible Evidence of a Termination Shock''
* [https://ui.adsabs.harvard.edu/abs/2021ApJ...910...40Z/abstract Zhang et al. (2021), ApJ, 910, 40] ''Multiwavelength Observations of the Formation and Eruption of a Complex Filament''
* [https://ui.adsabs.harvard.edu/abs/2020ApJ...904...94S/abstract Sharma et al. (2020), ApJ, 904, 94] ''Radio and X-Ray Observations of Short-lived Episodes of Electron Acceleration in a Solar Microflare''
* [https://ui.adsabs.harvard.edu/abs/2019ApJ...884...63C/abstract Chen et al. (2019), ApJ, 884, 63] ''Radio Spectroscopic Imaging of a Solar Flare Termination Shock: Split-band Feature as Evidence for Shock Compression''
* [https://ui.adsabs.harvard.edu/abs/2019ApJ...872...71Y/abstract Yu & Chen (2019), ApJ, 872, 71] ''Possible Detection of Subsecond-period Propagating Magnetohydrodynamics Waves in Post-reconnection Magnetic Loops during a Two-ribbon Solar Flare''
* [https://ui.adsabs.harvard.edu/abs/2018ApJ...866...62C/abstract Chen et al. (2018), ApJ, 866, 62] ''Magnetic Reconnection Null Points as the Origin of Semirelativistic Electron Beams in a Solar Jet
''
* [https://ui.adsabs.harvard.edu/abs/2017ApJ...848...77W/abstract Wang et al. (2016), ApJ, 848, 77] ''Dynamic Spectral Imaging of Decimetric Fiber Bursts in an Eruptive Solar Flare''
* [https://ui.adsabs.harvard.edu/abs/2015Sci...350.1238C/abstract Chen et al. (2015), Science, 350, 1238] ''Particle acceleration by a solar flare termination shock''
* [https://ui.adsabs.harvard.edu/abs/2014ApJ...794..149C/abstract Chen et al. (2014), ApJ, 794, 149] ''Direct Evidence of an Eruptive, Filament-hosting Magnetic Flux Rope Leading to a Fast Solar Coronal Mass Ejection''
* [https://ui.adsabs.harvard.edu/abs/2013ApJ...763L..21C/abstract Chen et al. (2013), ApJL, 763, 21] ''Tracing Electron Beams in the Sun's Corona with Radio Dynamic Imaging Spectroscopy''

==Radio Data from Around The Heliosphere==
* [http://ovsa.njit.edu//wiki/index.php/Radio_Data_from_Around_the_World#Radio_Data_Access '' Radio Data '']

=OVRO-LWA Solar-Dedicated Spectroscopic Imager=
The OVRO-LWA (Owens Valley Radio Observatory Long Wavelength Array) has recently been upgraded to include a solar-dedicated beam and two solar imaging modes (slow visibilities of 352 antennas with a 10-s cadence, and fast visibilities of 48 antennas with a 0.1-s cadence). The large collecting area and excellent calibration provide unprecedented high-sensitivity imaging of the quiet Sun and bursts. The array is currently in commissioning and observations are not yet continuous, but they are becoming more so. See the daily realtime data at http://ovsa.njit.edu/status.php for '''real-time display of the spectrogram and a selection of images''', both updated on a 1-min cadence.

==Solar-Dedicated Modes==
===Beamformer===
The beamformer uses the 256 core antennas to form a synthesized beam of more than 1 degree in size that tracks the Sun from sunrise to sunset. This permits a continuous record of the full-Stokes total flux (without spatial resolution) of the Sun (a dynamic spectrum) with 24 kHz frequency resolution (3072 frequencies from 15-90 MHz) and as low as 1 ms time resolution.

===Slow Visibility Imaging===
In this mode, the entire 352-element array is interferometrically correlated to provide visibilities for imaging at all 3072 frequencies at 10-s time resolution. This is ideal for imaging quiet Sun and slowly-varying emission such as coronal mass ejections and active region variability.

===Fast Visibility Imaging===
In this mode, a subset of 48 antennas (chosen to include mainly outer antennas to maintain good spatial resolution) is interferometrically correlated to provide visibilities for imaging at 768 frequencies (96 kHz frequency resolution) at 0.1-s time resolution. This is ideal for imaging rapidly varying emission such as type II and type III bursts as well as many other solar spectral fine structures.

==Inital Data Access==
In its current commissioning state, we try to run the beamformer and imaging pipeline every day in real-time since November 2023 (no latency for beamforming spectrograms and 5-10 min latency for images). Quicklook real-time spectrograms/images can be accessed from http://ovsa.njit.edu/status.php. To access data from previous days, use the following links (replace yyyymmdd with the date you desire):
* Quicklook beamformer total-power spectrograms: http://ovsa.njit.edu/lwa-data/1min_spectra/yyyymmdd/. Check this link for additional daily plots [[Daily OVRO-LWA Beamformer Data]].
* Quicklook multi-frequency movies at 1-min cadence: http://ovsa.njit.edu/lwa-data/1min_images/yyyymmdd/movie_yyyy-mm-dd.html

Note our pipeline processing development is still in the early phase. For example, absolute flux calibrations have not been done for the beamformer spectrograms. Also, artificial effects (including ionospheric refraction effects) are present in the images that cause distortions/shifts. We caution interested users only to consider them for quick-look purposes at this point. Please contact the EOVSA PIs (Dale Gary, Bin Chen) if you intend to use them for science.

==Operation Notes==
===Starting solar beamforming observations===
* Log into lwacalim10
* Activate the deployment conda environment
<pre> conda activate deploy </pre>
* Check what schedules are there
<pre>
lwaobserving show-schedule
</pre>
* Submit the schedule for the next 7 days
<pre>
cd /home/dgary
import make_solar_sdf
make_solar_sdf.multiday_obs(ndays=7)
</pre>
* Calibrate the beam
<pre>
cd /home/pipeline/proj/lwa-shell/mnc_python/
ipython
from mnc import control
con=control.Controller('/opt/devel/dgary/lwa_config_calim_std.yaml')
con.configure_xengine(['dr2'], calibratebeams=True)
</pre>

Owens Valley Solar Arrays

2024-05-28T21:40:13Z

Binchen:

[[File:Eovsa1.png|border|text-top|800px]]

<big>[http://ovsa.njit.edu/ EOVSA] (Expanded Owens Valley Solar Array) is a solar-dedicated radio interferometer operated by the New Jersey Institute of Technology and serving as a '''National Science Foundation Geospace Facility'''. [[File:NSF.jpg|70px]]
<pre>Operation of EOVSA is supported by the National Science Foundation under Grant No. AGS-2130832. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. </pre>
This wiki serves as the site for EOVSA documentation. </big>

[[File:OVRO-LWA1.png|border|text-top|800px]]

<big>OVRO-LWA (Owens Valley Radio Observatory Long Wavelength Array) is an all-sky imager that has a new solar-dedicated spectroscopic imaging mode. OVRO-LWA is a multi-institutional collaboration led by Caltech. NJIT Solar Radio Group is leading its solar-mode development and science. At the bottom of this page are new links for that facility. </big>

== EOVSA Flare List ==

* [https://ovsa.njit.edu/flarelist Query EOVSA Flare list]
* List of EOVSA flares in separate years: [[2024]], [[2023]], [[2022]], [[2021]], [[2020]], [[2019]]

== Using EOVSA Data ==
* <big>[[EOVSA Data products]]</big>: An introduction to standard EOVSA spectrogram and spectral image products with example scripts for reading and plotting.
* <big>[[EOVSA Data Policy]]</big>: Policy for using EOVSA data products.
* <big>Analysis Software</big>: These are for in-depth use of EOVSA data (from calibrated visibilities) and tools for quantitative analysis.
** [https://github.com/suncasa/suncasa SunCASA] A wrapper around [https://casa.nrao.edu/ CASA (the Common Astronomy Software Applications package)] for synthesis imaging and visualizing solar spectral imaging data. CASA is one of the leading software tool for "supporting the data post-processing needs of the next generation of radio astronomical telescopes such as ALMA and VLA", an international effort led by the [https://public.nrao.edu/ National Radio Astronomy Observatory]. The current version of CASA uses Python (2.7) interface. More information about CASA can be found on [https://casa.nrao.edu/ NRAO's CASA website ]. Note, CASA is available ONLY on UNIX-BASED PLATFORMS (and therefore, so is SunCASA).
** [https://github.com/Gelu-Nita/GSFIT GSFIT] A IDL-widget(GUI)-based spectral fitting package called gsfit, which provides a user-friendly display of EOVSA image cubes and an interface to fast fitting codes (via platform-dependent shared-object libraries).
** [https://github.com/suncasa/pygsfit pyGSFIT] A Python-widget(pyQT)-based spectral fitting package, which provides a user-friendly display of EOVSA image cubes, spatially resolved spectra, and an interface to scipy-based fitting codes.
** [[Spectrogram Software]]
** [[Mapping Software]]
* <big>Data Analysis Guides</big>
** <big>[[EOVSA Data Analysis Tutorial 2022]]</big> and <big>[https://colab.research.google.com/drive/19NQb6Emb9HvKX4QHq9ZYCP3RM6nT7sDL#scrollTo=cLdDVptBGG-X EOVSA Workspace]</big> at [https://sphere.boulder.swri.edu/ SPHERE 2022 Workshop]
** <big>[https://colab.research.google.com/drive/1lSLLxgOG6b8kgu9Sk6kSKvrViyubnXG6?usp=sharing#scrollTo=xbXyyLmCFCGL EOVSA Data Analysis Tutorial at RHESSI 19 Workshop]</big>
** <big>[[EOVSA Data Analysis Tutorial]]</big> at [http://rhessi18.umn.edu/ RHESSI XVIII Workshop]
** [[Self-Calibrating Flare Data]] Example script and guides for self-calibrating EOVSA flare data (to be completed)


**[[IDB flare pipeline]] Tutorial to run the flare pipeline for quicklook images



* <big>EOVSA Modeling Guide</big>
**[[GX Simulator]]

* Other helpful links
** [https://casaguides.nrao.edu CASA Guides]
** [http://www.lmsal.com/solarsoft/ SolarSoft IDL]
** [http://www.atnf.csiro.au/computing/software/miriad/userguide/userhtml.html Miriad Guides]
** [https://sites.google.com/site/fgscodes/ Fast Gyrosynchrotron Codes (Alexey Kuznetsov's website)]
** [[Basic GitHub Tutorial]]


* <big>[[Full Disk Simulations]]</big>
* <big>[[All-Day Synthesis Issues]]</big>
* <big>[[Analyzing Pre-2017 Data]]</big>
* <big>[[Fixing Pipeline Problems pre-2021-Feb-07]]</big>

== EOVSA Documentation ==

* <big>General</big>
** [[Downconversion and Frequency Tuning]]
** [[Dealing with Radio Frequency Interference]]
** [[Switching between 200 MHz and 300 MHz Correlator]]
** [[Observing in "Fast" Mode]]

* <big>Computer-Network</big>
** [[Computing Systems]]
** [[Network]]

* <big>Control System</big>
** [[27-m Antenna Commands]]
** [[Schedule Commands]]
** [[Control Commands]]
** [[Attenuation and Level Control]]

* <big>Hardware</big>
** [[Hardware Overview]]
** [[2.1-m Antennas]]
** [[27-m Antennas]]

* <big>System Software</big>
** [[Calibration Database]]
** [[Stateframe Database]]
** [[Database Maintenance]]
** [[Create CASA measurement sets]]

* <big>Calibration</big>
**[[Calibration Overview]]
**[[Pointing Calibration]]
**[[Total Power Calibration]]
**[[System Gain Calibration]]
**[[Antenna Position]] (Baseline Calibration)
**[[Reference Gain Calibration]]
**[[Daily Gain Calibration]]
**[[Delay Calibration]]
**[[Bandpass Calibration]]
**[[Polarization Calibration]]
**[[Calibrator Survey]]
**[[Practical Calibration Tutorial]]

* <big>[[Starburst]]</big>

== System Software ==

* LabVIEW software
* Python code [https://github.com/dgary50/eovsa Github repository]
* [[Python3 Code Installation]]

== EOVSA Observing Log ==
[[2016 November]]; [[2016 December| December]]

[[2017 January]]; [[2017 February | February]]; [[2017 March | March]]; [[2017 April | April]]; [[2017 May | May]]; [[2017 June | June]];
[[2017 July | July]]; [[2017 August | August]]; [[2017 September | September]]; [[2017 October | October]]; [[2017 November | November]]; [[2017 December | December]]

[[2018 January]]; [[2018 February | February]]; [[2018 March | March]]; [[2018 April | April]]; [[2018 May | May]]; [[2018 June | June]];
[[2018 July | July]]; [[2018 August | August]]; [[2018 September | September]]; [[2018 October | October]]; [[2018 November | November]]; [[2018 December | December]]

[[2019 January]]; [[2019 February | February]]; [[2019 March | March]]; [[2019 April | April]]; [[2019 May | May]]; [[2019 June | June]];
[[2019 July | July]]; [[2019 August | August]]; [[2019 September | September]]; [[2019 October | October]]; [[2019 November | November]]; [[2019 December | December]]

[[2020 January]]; [[2020 February | February]]; [[2020 March | March]]; [[2020 April | April]]; [[2020 May | May]]; [[2020 June | June]];
[[2020 July | July]]; [[2020 August | August]]; [[2020 September | September]]; [[2020 October | October]]; [[2020 November | November]]; [[2020 December | December]]

[[2021 January]]; [[2021 February | February]]; [[2021 March | March]]; [[2021 April | April]]; [[2021 May | May]]; [[2021 June | June]];
[[2021 July | July]]; [[2021 August | August]]; [[2021 September | September]]; [[2021 October | October]]; [[2021 November | November]]; [[2021 December | December]]

[[2022 SQL Outage]]

[[2023 January]]; [[2023 February | February]]; [[2023 March | March]]; [[2023 April | April]]; [[2023 May | May]]; [[2023 June | June]];
[[2023 July | July]]; [[2023 August | August]]; [[2023 September | September]]; [[2023 October | October]]; [[2023 November | November]]; [[2023 December | December]]

[[2024 January]]; [[2024 February | February]]; [[2024 March | March]];[[2024 April | April]];[[2024 May |May]]

== SoD Observing Logs ==
* See [https://docs.google.com/document/d/1_iGnMRRrvb85Z0vT8-LzgQmCOKDSATEuQ0vTsn2C-dc/edit?usp=sharing SoD Routines] for detailed instructions for Scientist-on-Duty routines.
* 2024 [https://docs.google.com/document/d/1QDWw5y4HpcE7CSpzXwftMqQT4FDgNJj-6fRrgWrqdug/edit?usp=sharing May], [https://docs.google.com/document/d/1Rh2gYBV2E454xVYEv8jx5IXKd1N2Z05ns4dhI2XCE08/edit?usp=sharing June], July, August, September, October, November, December

== Tohbans ==

[[Trouble Shooting Guide]]

[[Tohban Records]]

[[Owen's Notes]]

[[Caius' Notes]]

[[Tohban EOVSA Imaging Tutorial A-Z]]

[[Tohban OVRO-LWA Imaging Tutorial]]

[[Tohban Guide to Self Calibration and Imaging for EOVSA]]

[[Guide to Upgrade SolarSoft(SSW)]]

== EOVSA Publications ==
Here is a (partial) list of publications that utilize EOVSA data. See also the collection of EOVSA publications at [https://ui.adsabs.harvard.edu/public-libraries/eQ7HfPkySqydu-B8BCt6QQ this NASA/ADS Library].
; 2024
: Collier, H., Hayes, L. A., Yu, S., Battaglia, A. F., Ashfield, W., Polito, V., Harra, L. K., & Krucker, S. (2024), arXiv e-prints, arXiv:2402.10546. [https://ui.adsabs.harvard.edu/abs/2024arXiv240210546C “Localising pulsations in the hard X-ray and microwave emission of an X-class flare”]
: Saqri, J., Veronig, A. M., Battaglia, A. F., Dickson, E. C. M., Gary, D. E., & Krucker, S. (2024), Astronomy and Astrophysics, 683, A41. [https://ui.adsabs.harvard.edu/abs/2024A&A...683A..41S "Efficiency of solar microflares in accelerating electrons when rooted in a sunspot"]
; 2023
: Tan, B., Yan, Y., Huang, J., Zhang, Y., Tan, C., & Zhu, X. (2023), Advances in Space Research, 72, 5563. [https://ui.adsabs.harvard.edu/abs/2023AdSpR..72.5563T "The physics of solar spectral imaging observations in dm-cm wavelengths and the application on space weather"]

: Li, D., Li, Z., Shi, F., Su, Y., Chen, W., Yu, F., Li, C., Qiu, Y., Huang, Y., & Ning, Z. (2023), Astronomy and Astrophysics, 680, L15. [https://ui.adsabs.harvard.edu/abs/2023A&A...680L..15L "Observational signature of continuously operating drivers of decayless kink oscillation"]

: Wang, M., Chen, B., Yu, S., Gary, D. E., Lee, J., Wang, H., & Cohen, C. (2023), The Astrophysical Journal, 954, 32. [https://ui.adsabs.harvard.edu/abs/2023ApJ...954...32W "The Solar Origin of an In Situ Type III Radio Burst Event"]

: Gary, D. E. (2023), Annual Review of Astronomy and Astrophysics, 61, 427. [https://ui.adsabs.harvard.edu/abs/2023ARA&A..61..427G "New Insights from Imaging Spectroscopy of Solar Radio Emission"]

: Nita, G. M., Fleishman, G. D., Kuznetsov, A. A., Anfinogentov, S. A., Stupishin, A. G., Kontar, E. P., Schonfeld, S. J., Klimchuk, J. A., & Gary, D. E. (2023), The Astrophysical Journal Supplement Series, 267, 6. [https://ui.adsabs.harvard.edu/abs/2023ApJS..267....6N "Data-constrained Solar Modeling with GX Simulator"]

: Song, D.-C., Tian, J., Li, Y., Ding, M. D., Su, Y., Yu, S., Hong, J., Qiu, Y., Rao, S., Liu, X., Li, Q., Chen, X., Li, C., & Fang, C. (2023), The Astrophysical Journal, 952, L6. [https://ui.adsabs.harvard.edu/abs/2023ApJ...952L...6S "Spectral Observations and Modeling of a Solar White-light Flare Observed by CHASE"]

: Mondal, S., Chen, B., & Yu, S. (2023), The Astrophysical Journal, 949, 56. [https://ui.adsabs.harvard.edu/abs/2023ApJ...949...56M "Multifrequency Microwave Imaging of Weak Transients from the Quiet Solar Corona"]

: Kontar, E. P., Emslie, A. G., Motorina, G. G., & Dennis, B. R. (2023), The Astrophysical Journal, 947, L13. [https://ui.adsabs.harvard.edu/abs/2023ApJ...947L..13K "The Efficiency of Electron Acceleration during the Impulsive Phase of a Solar Flare"]

: Saqri, J., Veronig, A. M., Dickson, E. C. M., Podladchikova, T., Warmuth, A., Xiao, H., Gary, D. E., Battaglia, A. F., & Krucker, S. (2023), Astronomy and Astrophysics, 672, A23. [https://ui.adsabs.harvard.edu/abs/2023A&A...672A..23S "Multi-point study of the energy release and impulsive CME dynamics in an eruptive C7 flare"]
; 2022

: Kou, Y., Cheng, X., Wang, Y., Yu, S., Chen, B., Kontar, E. P., & Ding, M. (2022), Nature Communications, 13, 7680. [https://ui.adsabs.harvard.edu/abs/2022NatCo..13.7680K "Microwave imaging of quasi-periodic pulsations at flare current sheet"]

: Chertok, I. M. (2022), Monthly Notices of the Royal Astronomical Society, 517, 2709. [https://ui.adsabs.harvard.edu/abs/2022MNRAS.517.2709C "On some features of the solar proton event on 2021 October 28 - GLE73"]

: Lörinčík, J., Polito, V., De Pontieu, B., Yu, S., & Freij, N. (2022), Frontiers in Astronomy and Space Sciences, 9, 334. [https://ui.adsabs.harvard.edu/abs/2022FrASS...940945L "Rapid variations of Si IV spectra in a flare observed by interface region imaging spectrograph at a sub-second cadence"]

: Klein, K.-L., Musset, S., Vilmer, N., Briand, C., Krucker, S., Francesco Battaglia, A., Dresing, N., Palmroos, C., & Gary, D. E. (2022), Astronomy and Astrophysics, 663, A173. [https://ui.adsabs.harvard.edu/abs/2022A&A...663A.173K "The relativistic solar particle event on 28 October 2021: Evidence of particle acceleration within and escape from the solar corona"]

: Fleishman, G. D., Nita, G. M., Chen, B., Yu, S., & Gary, D. E. (2022), Nature, 606, 674. [https://ui.adsabs.harvard.edu/abs/2022Natur.606..674F "Solar flare accelerates nearly all electrons in a large coronal volume"]

: Li, X., Guo, F., Chen, B., Shen, C., & Glesener, L. (2022), The Astrophysical Journal, 932, 92. [https://ui.adsabs.harvard.edu/abs/2022ApJ...932...92L "Modeling Electron Acceleration and Transport in the Early Impulsive Phase of the 2017 September 10th Solar Flare"]

: Zhang, J., Chen, B., Yu, S., Tian, H., Wei, Y., Chen, H., Tan, G., Luo, Y., & Chen, X. (2022), The Astrophysical Journal, 932, 53. [https://ui.adsabs.harvard.edu/abs/2022ApJ...932...53Z "Implications for Additional Plasma Heating Driving the Extreme-ultraviolet Late Phase of a Solar Flare with Microwave Imaging Spectroscopy"]

: Liu, N., Jing, J., Xu, Y., & Wang, H. (2022), The Astrophysical Journal, 930, 154. [https://ui.adsabs.harvard.edu/abs/2022ApJ...930..154L "Multi-instrument Comparative Study of Temperature, Number Density, and Emission Measure during the Precursor Phase of a Solar Flare"]

: López, F. M., Giménez de Castro, C. G., Mandrini, C. H., Simões, P. J. A., Cristiani, G. D., Gary, D. E., Francile, C., & Démoulin, P. (2022), Astronomy and Astrophysics, 657, A51. [https://ui.adsabs.harvard.edu/abs/2022A&A...657A..51L "A solar flare driven by thermal conduction observed in mid-infrared"]

: Unverferth, J., & Longcope, D. (2021), The Astrophysical Journal, 923, 248. [https://ui.adsabs.harvard.edu/abs/2021ApJ...923..248U "Examining Flux Tube Interactions as a Cause of Sub-alfvénic Outflow"]
;2021

: Wei, Y., Chen, B., Yu, S., Wang, H., Jing, J., & Gary, D. E. (2021), The Astrophysical Journal, 923, 213. [https://ui.adsabs.harvard.edu/abs/2021ApJ...923..213W "Coronal Magnetic Field Measurements along a Partially Erupting Filament in a Solar Flare"]

: Jing, J., Inoue, S., Lee, J., Li, Q., Nita, G. M., Xu, Y., Liu, C., Gary, D. E., & Wang, H. (2021), The Astrophysical Journal, 922, 108. [https://ui.adsabs.harvard.edu/abs/2021ApJ...922..108J "Understanding the Initiation of the M2.4 Flare on 2017 July 14"]

: Battaglia, A. F., Saqri, J., Massa, P., Perracchione, E., Dickson, E. C. M., Xiao, H., Veronig, A. M., Warmuth, A., Battaglia, M., Hurford, G. J., Meuris, A., Limousin, O., Etesi, L., Maloney, S. A., Schwartz, R. A., Kuhar, M., Schuller, F., Senthamizh Pavai, V., Musset, S., Ryan, D. F., Kleint, L., Piana, M., Massone, A. M., Benvenuto, F., Sylwester, J., Litwicka, M., Stȩślicki, M., Mrozek, T., Vilmer, N., Fárník, F., Kašparová, J., Mann, G., Gallagher, P. T., Dennis, B. R., Csillaghy, A., Benz, A. O., & Krucker, S. (2021), Astronomy and Astrophysics, 656, A4. [https://ui.adsabs.harvard.edu/abs/2021A&A...656A...4B "STIX X-ray microflare observations during the Solar Orbiter commissioning phase"]

: Shaik, S. B., & Gary, D. E. (2021), The Astrophysical Journal, 919, 44. [https://ui.adsabs.harvard.edu/abs/2021ApJ...919...44S "Implications of Flat Optically Thick Microwave Spectra in Solar Flares for Source Size and Morphology"]

: Kocharov, L., Omodei, N., Mishev, A., Pesce-Rollins, M., Longo, F., Yu, S., Gary, D. E., Vainio, R., & Usoskin, I. (2021), The Astrophysical Journal, 915, 12. [https://ui.adsabs.harvard.edu/abs/2021ApJ...915...12K "Multiple Sources of Solar High-energy Protons"]

: Chen, B., Battaglia, M., Krucker, S., Reeves, K. K., & Glesener, L. (2021), The Astrophysical Journal, 908, L55. [https://ui.adsabs.harvard.edu/abs/2021ApJ...908L..55C "Energetic Electron Distribution of the Coronal Acceleration Region: First Results from Joint Microwave and Hard X-Ray Imaging Spectroscopy"]

: Chhabra, S., Gary, D. E., Hallinan, G., Anderson, M. M., Chen, B., Greenhill, L. J., & Price, D. C. (2021), The Astrophysical Journal, 906, 132. [https://ui.adsabs.harvard.edu/abs/2021ApJ...906..132C "Imaging Spectroscopy of CME-associated Solar Radio Bursts using OVRO-LWA"]
;2020 and earlier

: Reeves, K. K., Polito, V., Chen, B., Galan, G., Yu, S., Liu, W., & Li, G. (2020), The Astrophysical Journal, 905, 165. [https://ui.adsabs.harvard.edu/abs/2020ApJ...905..165R "Hot Plasma Flows and Oscillations in the Loop-top Region During the 2017 September 10 X8.2 Solar Flare"]

: Nindos, A. (2020), Frontiers in Astronomy and Space Sciences, 7, 57. [https://ui.adsabs.harvard.edu/abs/2020FrASS...7...57N "Incoherent Solar Radio Emission"]

: Yu, S., Chen, B., Reeves, K. K., Gary, D. E., Musset, S., Fleishman, G. D., Nita, G. M., & Glesener, L. (2020), The Astrophysical Journal, 900, 17. [https://ui.adsabs.harvard.edu/abs/2020ApJ...900...17Y "Magnetic Reconnection during the Post-impulsive Phase of a Long-duration Solar Flare: Bidirectional Outflows as a Cause of Microwave and X-Ray Bursts"]

: Chen, B., Yu, S., Reeves, K. K., & Gary, D. E. (2020), The Astrophysical Journal, 895, L50. [https://ui.adsabs.harvard.edu/abs/2020ApJ...895L..50C "Microwave Spectral Imaging of an Erupting Magnetic Flux Rope: Implications for the Standard Solar Flare Model in Three Dimensions"]

: Kuroda, N., Fleishman, G. D., Gary, D. E., Nita, G. M., Chen, B., & Yu, S. (2020), Frontiers in Astronomy and Space Sciences, 7, 22. [https://ui.adsabs.harvard.edu/abs/2020FrASS...7...22K "Evolution of Flare-accelerated Electrons Quantified by Spatially Resolved Analysis"]

: Glesener, L., Krucker, S., Duncan, J., Hannah, I. G., Grefenstette, B. W., Chen, B., Smith, D. M., White, S. M., & Hudson, H. (2020), The Astrophysical Journal, 891, L34. [https://ui.adsabs.harvard.edu/abs/2020ApJ...891L..34G "Accelerated Electrons Observed Down to <7 keV in a NuSTAR Solar Microflare"]

: Karlický, M., Chen, B., Gary, D. E., Kašparová, J., & Rybák, J. (2020), The Astrophysical Journal, 889, 72. [https://ui.adsabs.harvard.edu/abs/2020ApJ...889...72K "Drifting Pulsation Structure at the Very Beginning of the 2017 September 10 Limb Flare"]

: Fleishman, G. D., Gary, D. E., Chen, B., Kuroda, N., Yu, S., & Nita, G. M. (2020), Science, 367, 278. [https://ui.adsabs.harvard.edu/abs/2020Sci...367..278F "Decay of the coronal magnetic field can release sufficient energy to power a solar flare"]

: Chen, B., Shen, C., Gary, D. E., Reeves, K. K., Fleishman, G. D., Yu, S., Guo, F., Krucker, S., Lin, J., Nita, G. M., & Kong, X. (2020), Nature Astronomy, 4, 1140. [https://ui.adsabs.harvard.edu/abs/2020NatAs...4.1140C "Measurement of magnetic field and relativistic electrons along a solar flare current sheet"]

: Lee, J. (2018), Journal of Astronomy and Space Sciences, 35, 211. [https://ui.adsabs.harvard.edu/abs/2018JASS...35..211L "Analysis of Solar Microwave Burst Spectrum, I. Nonuniform Magnetic Field"]

: Gary, D. E., Bastian, T. S., Chen, B., Fleishman, G. D., & Glesener, L. (2018), Science with a Next Generation Very Large Array, 517, 99. [https://ui.adsabs.harvard.edu/abs/2018ASPC..517...99G "Radio Observations of Solar Flares"]

: Polito, V., Dudík, J., Kašparová, J., Dzifčáková, E., Reeves, K. K., Testa, P., & Chen, B. (2018), The Astrophysical Journal, 864, 63. [https://ui.adsabs.harvard.edu/abs/2018ApJ...864...63P "Broad Non-Gaussian Fe XXIV Line Profiles in the Impulsive Phase of the 2017 September 10 X8.3-class Flare Observed by Hinode/EIS"]

: Gary, D. E., Chen, B., Dennis, B. R., Fleishman, G. D., Hurford, G. J., Krucker, S., McTiernan, J. M., Nita, G. M., Shih, A. Y., White, S. M., & Yu, S. (2018), The Astrophysical Journal, 863, 83. [https://ui.adsabs.harvard.edu/abs/2018ApJ...863...83G "Microwave and Hard X-Ray Observations of the 2017 September 10 Solar Limb Flare"]

: Fleishman, G. D., Nita, G. M., Kuroda, N., Jia, S., Tong, K., Wen, R. R., & Zhizhuo, Z. (2018), The Astrophysical Journal, 859, 17. [https://ui.adsabs.harvard.edu/abs/2018ApJ...859...17F "Revealing the Evolution of Non-thermal Electrons in Solar Flares Using 3D Modeling"]

: Kuroda, N., Gary, D. E., Wang, H., Fleishman, G. D., Nita, G. M., & Jing, J. (2018), The Astrophysical Journal, 852, 32. [https://ui.adsabs.harvard.edu/abs/2018ApJ...852...32K "Three-dimensional Forward-fit Modeling of the Hard X-Ray and Microwave Emissions of the 2015 June 22 M6.5 Flare"]

: Wang, H., Liu, C., Ahn, K., Xu, Y., Jing, J., Deng, N., Huang, N., Liu, R., Kusano, K., Fleishman, G. D., Gary, D. E., & Cao, W. (2017), Nature Astronomy, 1, 0085. [https://ui.adsabs.harvard.edu/abs/2017NatAs...1E..85W "High-resolution observations of flare precursors in the low solar atmosphere"]

: Nita, G. M., Hickish, J., MacMahon, D., & Gary, D. E. (2016), Journal of Astronomical Instrumentation, 5, 1641009-7366. [https://ui.adsabs.harvard.edu/abs/2016JAI.....541009N "EOVSA Implementation of a Spectral Kurtosis Correlator for Transient Detection and Classification"]

: Nita, G. M., & Gary, D. E. (2016), Journal of Geophysical Research (Space Physics), 121, 7353. [https://ui.adsabs.harvard.edu/abs/2016JGRA..121.7353N "Measurement of duration and signal-to-noise ratio of astronomical transients using a Spectral Kurtosis spectrometer"]

: Wang, Z., Gary, D. E., Fleishman, G. D., & White, S. M. (2015), The Astrophysical Journal, 805, 93. [https://ui.adsabs.harvard.edu/abs/2015ApJ...805...93W "Coronal Magnetography of a Simulated Solar Active Region from Microwave Imaging Spectropolarimetry"]

: Gary, D. E., Fleishman, G. D., & Nita, G. M. (2013), Solar Physics, 288, 549. [https://ui.adsabs.harvard.edu/abs/2013SoPh..288..549G "Magnetography of Solar Flaring Loops with Microwave Imaging Spectropolarimetry"]

== VLA Flare List and Publications ==
See [http://www.ovsa.njit.edu/wiki/index.php/VLA_Data_Survey#List_of_Jansky_VLA_Solar_Observations this link] for a list of flare observations made by the [https://science.nrao.edu/facilities/vla/ Karl G. Jansky Very Large Array] (VLA). Below is a partial list of publications that utilize VLA solar data (see also [https://ui.adsabs.harvard.edu/public-libraries/ZwbjpLo9RS-viufWEoQ95Q this NASA/ADS Library]).
* [https://ui.adsabs.harvard.edu/abs/2022ApJ...940..137L/abstract Luo et al. (2022), ApJ, 940, 137] ''Multiple Regions of Nonthermal Quasiperiodic Pulsations during the Impulsive Phase of a Solar Flare''
* [https://ui.adsabs.harvard.edu/abs/2021ApJ...922..134B/abstract Battaglia et al. (2021), ApJ, 922, 134] ''Multiple Electron Acceleration Instances during a Series of Solar Microflares Observed Simultaneously at X-Rays and Microwaves''
* [https://ui.adsabs.harvard.edu/abs/2021ApJ...911....4L/abstract Luo et al. (2021), ApJ, 911, 4] ''Radio Spectral Imaging of an M8.4 Eruptive Solar Flare: Possible Evidence of a Termination Shock''
* [https://ui.adsabs.harvard.edu/abs/2021ApJ...910...40Z/abstract Zhang et al. (2021), ApJ, 910, 40] ''Multiwavelength Observations of the Formation and Eruption of a Complex Filament''
* [https://ui.adsabs.harvard.edu/abs/2020ApJ...904...94S/abstract Sharma et al. (2020), ApJ, 904, 94] ''Radio and X-Ray Observations of Short-lived Episodes of Electron Acceleration in a Solar Microflare''
* [https://ui.adsabs.harvard.edu/abs/2019ApJ...884...63C/abstract Chen et al. (2019), ApJ, 884, 63] ''Radio Spectroscopic Imaging of a Solar Flare Termination Shock: Split-band Feature as Evidence for Shock Compression''
* [https://ui.adsabs.harvard.edu/abs/2019ApJ...872...71Y/abstract Yu & Chen (2019), ApJ, 872, 71] ''Possible Detection of Subsecond-period Propagating Magnetohydrodynamics Waves in Post-reconnection Magnetic Loops during a Two-ribbon Solar Flare''
* [https://ui.adsabs.harvard.edu/abs/2018ApJ...866...62C/abstract Chen et al. (2018), ApJ, 866, 62] ''Magnetic Reconnection Null Points as the Origin of Semirelativistic Electron Beams in a Solar Jet
''
* [https://ui.adsabs.harvard.edu/abs/2017ApJ...848...77W/abstract Wang et al. (2016), ApJ, 848, 77] ''Dynamic Spectral Imaging of Decimetric Fiber Bursts in an Eruptive Solar Flare''
* [https://ui.adsabs.harvard.edu/abs/2015Sci...350.1238C/abstract Chen et al. (2015), Science, 350, 1238] ''Particle acceleration by a solar flare termination shock''
* [https://ui.adsabs.harvard.edu/abs/2014ApJ...794..149C/abstract Chen et al. (2014), ApJ, 794, 149] ''Direct Evidence of an Eruptive, Filament-hosting Magnetic Flux Rope Leading to a Fast Solar Coronal Mass Ejection''
* [https://ui.adsabs.harvard.edu/abs/2013ApJ...763L..21C/abstract Chen et al. (2013), ApJL, 763, 21] ''Tracing Electron Beams in the Sun's Corona with Radio Dynamic Imaging Spectroscopy''

==Radio Data from Around The Heliosphere==
* [http://ovsa.njit.edu//wiki/index.php/Radio_Data_from_Around_the_World#Radio_Data_Access '' Radio Data '']

=OVRO-LWA Solar-Dedicated Spectroscopic Imager=
The OVRO-LWA (Owens Valley Radio Observatory Long Wavelength Array) has recently been upgraded to include a solar-dedicated beam and two solar imaging modes (slow visibilities of 352 antennas with a 10-s cadence, and fast visibilities of 48 antennas with a 0.1-s cadence). The large collecting area and excellent calibration provide unprecedented high-sensitivity imaging of the quiet Sun and bursts. The array is currently in commissioning and observations are not yet continuous, but they are becoming more so. See the daily realtime data at http://ovsa.njit.edu/status.php for '''real-time display of the spectrogram and a selection of images''', both updated on a 1-min cadence.

==Solar-Dedicated Modes==
===Beamformer===
The beamformer uses the 256 core antennas to form a synthesized beam of more than 1 degree in size that tracks the Sun from sunrise to sunset. This permits a continuous record of the full-Stokes total flux (without spatial resolution) of the Sun (a dynamic spectrum) with 24 kHz frequency resolution (3072 frequencies from 15-90 MHz) and as low as 1 ms time resolution.

===Slow Visibility Imaging===
In this mode, the entire 352-element array is interferometrically correlated to provide visibilities for imaging at all 3072 frequencies at 10-s time resolution. This is ideal for imaging quiet Sun and slowly-varying emission such as coronal mass ejections and active region variability.

===Fast Visibility Imaging===
In this mode, a subset of 48 antennas (chosen to include mainly outer antennas to maintain good spatial resolution) is interferometrically correlated to provide visibilities for imaging at 768 frequencies (96 kHz frequency resolution) at 0.1-s time resolution. This is ideal for imaging rapidly varying emission such as type II and type III bursts as well as many other solar spectral fine structures.

==Inital Data Access==
In its current commissioning state, we try to run the beamformer and imaging pipeline every day in real-time since November 2023 (no latency for beamforming spectrograms and 5-10 min latency for images). Quicklook real-time spectrograms/images can be accessed from http://ovsa.njit.edu/status.php. To access data from previous days, use the following links (replace yyyymmdd with the date you desire):
* Quicklook beamformer total-power spectrograms: http://ovsa.njit.edu/lwa-data/1min_spectra/yyyymmdd/. Check this link for additional daily plots [[Daily OVRO-LWA Beamformer Data]].
* Quicklook multi-frequency movies at 1-min cadence: http://ovsa.njit.edu/lwa-data/1min_images/yyyymmdd/movie_yyyy-mm-dd.html

Note our pipeline processing development is still in the early phase. For example, absolute flux calibrations have not been done for the beamformer spectrograms. Also, artificial effects (including ionospheric refraction effects) are present in the images that cause distortions/shifts. We caution interested users only to consider them for quick-look purposes at this point. Please contact the EOVSA PIs (Dale Gary, Bin Chen) if you intend to use them for science.

OVSA Data Policy

2024-05-17T19:31:55Z

Binchen:

EOVSA data products are open to all scientists and the general public. Although we have an open data policy, the continued availability of EOVSA data relies on the proper acknowledgment of data and personnel support by its users. Guidelines for EOVSA data usage and publication policy are as follows:

=Contacting EOVSA team=
While EOVSA has an open data use policy (i.e., prior permission to access and analyze the data is not required), the data can be subject to limitations that are not immediately evident to users, and at times, the analysis and interpretation of the data involve more in-depth processing. Therefore, we encourage EOVSA data users to contact the EOVSA PIs ([mailto:dgary@njit.edu Dale Gary] and [mailto:bin.chen@njit.edu Bin Chen]) with a short description of your study and the data products that you intend to use. Contacting the PIs near the start of your project will allow us to:
* Direct you to EOVSA team member(s) who can offer assistance in processing and/or interpreting the data.
* Alert you of any instrumental effects that could possibly result in misinterpretation of EOVSA data products.

We request that EOVSA data users provide the EOVSA PIs with a link to a copy of any papers that include EOVSA data, on submission and again on publication.

=Acknowledgment, Citation, and Authorship=
All publications that use EOVSA data should include a statement in the Acknowledgments section as follows: "'''The Expanded Owens Valley Solar Array (EOVSA) was designed, built, and is now operated by the New Jersey Institute of Technology (NJIT) as a community facility. EOVSA operations are supported by NSF grant AGS-2130832 and NASA grant 80NSSC20K0026 to NJIT.'''" Because these grant numbers change from time to time, please check back to this page for updates.

For all publications that use EOVSA data, authors are asked to:
* Send a link to a copy of the paper to the EOVSA PIs Dale Gary and Bin Chen to keep a record of EOVSA publications.
* Cite the EOVSA first result paper Gary et al. 2018, “Microwave and Hard X-Ray Observations of the 2017 September 10 Solar Limb Flare,” ApJ, 863, 83 ([https://iopscience.iop.org/article/10.3847/1538-4357/aad0ef DOI]; [https://ui.adsabs.harvard.edu/abs/2018ApJ...863...83G/abstract NASA/SAO ADS]). [An EOVSA instrument paper and a pipeline processing paper are being prepared, which will be updated on this page.]

Additionally, for publications that involve more advanced data processing aided by EOVSA team member(s) or use special observing modes:
* Include EOVSA team member(s) in the author list who a) helped process/interpret the data and/or b) helped plan the observations. The authors are encouraged to check with the EOVSA PIs for authorship suggestions.

EOVSA Data Products

2024-03-29T21:09:29Z

Binchen: /* Synoptic Data Products */

=Introduction=
EOVSA observes the full disk of the Sun at all times when the Sun is >10 degrees above the local horizon (season dependent and ranges from 7-12 hours duration centered on 20 UT). EOVSA records data at 451 science frequency channels each second, in four polarization products, as well as additional total flux measurements from each individual antenna. Figure 1 summarizes the different levels of data we produce. The later sections will give a more detailed description and usage examples.
[[File:pipeline_flowchart.jpg|center|600px|EOVSA pipeline block diagram/flow chart ]]

=Level 0 - Raw visibility data from the instrument=

As outlined in Figure 1, EOVSA creates raw data products in the left-hand column (labeled Level 0). This includes observations of cosmic sources for phase calibration, and gain and pointing observations required for total power calibration.

==Raw "Interim" Database (IDB) visibility data==
Full-resolution raw "Interim" Database (IDB) visibility data. They are stored in Miriad format, and hence may not be that useful for most people. Be patient after clicking the link--this is a very long list of directories, one for each available date. Recent data (latest few months) can be retrieved from the following page:

https://www.ovsa.njit.edu/fits/IDB/

For older data, visit the UC/Berkeley hosting page:

https://research.ssl.berkeley.edu/data/eovsa/IDB/

==Raw 1-min-averaged visibility data==
This is the same as for the IDB data, except with 1-minute time integration applied. This is typically not useful for flares, but is perfectly fine for imaging active regions and full Sun. These data can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/UDB/

=Level 0.5 - Calibrated visibility data=
After applying calibration and other preliminary processing to the raw (level 0) data, we create the CASA ms’s in the second column in Figure 1 (labeled "level 0.5"). These visibility data are in the Fourier domain of the true images in the plane of the sky and are not immediately ready for spectral imaging analysis yet. However, they have all of the required content to produce images and spectrogram data in standard FITS format (level 1.0). We provide a set of standard ms’s for each day (red boxes in Figure 1), for use by researchers who know how to deal with visibility data. These data are more suitable for experienced users to exploit the full potential of EOVSA data, such as spatially resolved spectral analysis. Processing these data requires CASA or sunCASA (https://github.com/suncasa/suncasa-src). Please refer to our tutorial at [[EOVSA_Data_Analysis_Tutorial]].

==Calibrated full-resolution visibility data for flare events==
Calibrated and self-calibrated visibility data for flare events (purple boxes in Figure 1) will typically be available within 7 days after they are taken. They will be released at our flare list site soon: https://ovsa.njit.edu/flarelist

==Self-calibrated 1-min-averaged visibility data==
EOVSA 1-min averaged visibility data in CASA ms format can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/UDBms_slfcaled

=Level 1.0 - Images and spectrogram data in standard FITS format =

Level 1.0 data are for users who prefer to work with spectrogram (frequency-time) and image data directly, which are also outputs of the pipeline system shown in Figure 1 (orange boxes). They are perfectly suitable to be used as context data for comparison with other multi-wavelength observations but are not (yet) intended for quantitative spatially resolved spectral analysis.

Spectrograms are provided as standard FITS tables containing the frequency list, list of times, and data in both total power (TP) and a sum of amplitudes over intermediate-length baselines (cross power or XP). Likewise, image data products are in FITS format with standard keywords and are converted into the Helioprojective Cartesian coordinate system compatible with the World Coordinate System (WCS) convention, along with correct registration for the spatial, spectral, and temporal coordinates. Both the spectrogram and image data products are calibrated and have physical radio intensity units (sfu for spectrograms and brightness temperature for radio images).

We provide the following level 1 data products:
* Synoptic products:
** '''All-day spectrograms''': Full-day total-power (TP) and cross-power (XP) spectrograms (i.e., no spatial resolution) at full spectral and time resolution in FITS format. One file per day.
** '''All-day synoptic images''': Full disk images at 6 selected frequency bands centered at 1.4, 3.0, 4.5, 6.8, 10.2, and 13.9 GHz are produced once per day utilizing the earth-rotation synthesis, calibrated in brightness temperature. This is because EOVSA has a limited number of baselines and we need a long integration to fill up the uv domain in order to make full-disk images.
* Event-based products:
** '''Flare spectrograms''': These are full time and frequency resolution spectrograms produced from the median of calibrated cross-power visibilities in FITS format, cropped to cover the flare duration. Preflare background is also subtracted. Compared to total-power spectrograms, these spectrograms have the advantage of revealing details of the flare evolution by "filtering out" the large-scale, continuous background from the visibilities. Note that for certain flares that have a large source size, the flux can be lower than its true values (as a fraction of the flux will be "resolved out").
** '''Pipeline-produced spectral images''': We also have a semi-automated flare imaging pipeline to produce calibrated (and self-calibrated) images at 12-s cadence at up to 10 frequency bands. They are saved in standard FITS format and have been registered into Helioprojective coordinates. They can be read by SSWIDL or astropy/sunpy. These data have already been calibrated to physical units and are usually good to be compared with context data. But please be cautious when using them for quantitative spectral analysis.

{| class="wikitable"
|+ Summary of EOVSA Level 1 Data Products
|-
! scope="col"| Category
! scope="col"| Data Product
! scope="col"| Naming Convention
! scope="col"| Download Link
|-
! rowspan="2" | Synoptic Spectrograms
| All-day TP Spectrograms
| EOVSA_TPall_yyyymmdd.fts
!rowspan="9" | https://ovsa.njit.edu/browser
|-
| All-day XP Spectrograms
| EOVSA_XPall_yyyymmdd.fts
|-
! rowspan="7" | Synoptic Images
|-
| Synoptic 1.4 GHz images
| eovsa_yyyymmdd.spw00-01.tb.disk.fits
|-
| Synoptic 3.0 GHz images
| eovsa_yyyymmdd.spw02-05.tb.disk.fits
|-
| Synoptic 4.5 GHz images
| eovsa_yyyymmdd.spw06-10.tb.disk.fits
|-
| Synoptic 6.8 GHz images
| eovsa_yyyymmdd.spw11-20.tb.disk.fits
|-
| Synoptic 10.2 GHz images
| eovsa_yyyymmdd.spw21-30.tb.disk.fits
|-
| Synoptic 13.9 GHz images
| eovsa_yyyymmdd.spw31-43.tb.disk.fits
|-
! rowspan="1" | Flare Spectrograms
| Full-resolution cross-power Spectrogram
| eovsa.spec.flare_id_YYYYMMDDHHMMSS.fits
!rowspan="2" | https://ovsa.njit.edu/flarelist
|-
! rowspan="1" | Flare Spectral Images
| Pipeline-produced spectral images
| eovsa.lev1_mbd_12s.YYYY-MM-DDTHHMMSSZ.image.fits
|-
|}

==Browsing and Downloading level 1 data==
[[File:eovsa_browser.jpg|right|thumb|EOVSA Browser]]
[[file:EOVSA_flarelist.jpg|right|thumb|EOVSA Flare List]]
===Synoptic level 1 data===
EOVSA Level 1 synoptic data products can be retrieved with the following steps:
* Go to [http://ovsa.njit.edu/browser/ EOVSA browser] page.
* Browse to the date of interest.
* Click "synoptic fits" button next to the calendar tool.
* Select the data product based on the names listed in the table above.

===Flare level 1 data===
EOVSA flare list with spectrograms and spectral images can be queried and downloaded at https://ovsa.njit.edu/flarelist. Users can use the top box to select a time range of interest and query our flare list. The results are displayed in the dropdown box. An interactive plot of the flare light curves will be shown at the bottom of the page once an event is highlighted (by clicking on the flare ID). Quicklook plots and FITS files of the spectrograms and flare movies can be accessed by clicking the icons in each flare record.

==Reading and Using level 1 data==
===Introduction===
All our level 1 data products are in FITS format. All the images have standard, WCS-compatible coordinates. Users can use their favorite method to read these files. In the following, we provide minimal examples to read them with Astropy and Sunpy.

===Event-Based Data Products===
* An example of how to read and plot the flare spectrograms and images in Python (with [https://www.astropy.org/ Astropy] and [https://sunpy.org/ SunPy]) can be accessed at [https://colab.research.google.com/drive/1Y3ONWCxLPYvWda5_LqFNxafJtwZDNJBD?usp=sharing#scrollTo=ueiMoHbdxfo- this Google Colab Jupyter notebook].
* We are working on an example with SSWIDL and will post it soon.

===Synoptic Data Products===
* An example of how to read and plot the flare spectrograms and images in Python (with [https://www.astropy.org/ Astropy], [https://sunpy.org/ SunPy], and optionally, [https://docs.sunpy.org/projects/radiospectra/en/latest/ radiospectra]) can be accessed at [https://colab.research.google.com/drive/11vYHSA6YmaJm0Fl-lHXtNuV3Y6WEcif_#scrollTo=-qLxlKn90lSL this Google Colab Jupyter notebook].

Additional examples for IDL users. For spectrograms:
<pre style="background-color: #FCEBD9;">
function dspec,filename,doplot=doplot
; Read EOVSA Dynamic Spectrum FITS file <filename> and return a spectrogram object.
; Optionally show an overview plot if doplot switch is set
;
; Usage:
; s = dspec(<filename>) ; Returns spectrogram object
; s = dspec(<filename>,/doplot) ; Plots spectrum and returns spectrogram object
;
; To access the data in the spectrogram object, use
; spec = s.get(/spectrogram) (Array of amplitudes in SFU, of size ntimes, nfreq)
; fghz = s.get(/spectrum_axis) (Array of frequencies in GHz, of size nfreq)
; ut = s.get(/time_axis) (Array of UT times in anytim format, of size ntimes)

default,doplot,0
spec = mrdfits(filename,0)
freq = mrdfits(filename,1)
time = mrdfits(filename,2)
fghz = freq.sfreq
ut = anytim(time)
s = spectrogram(spec,ut,fghz)
if doplot then begin
window,/free,xsiz=1024,ysiz=600
; Find min and max of data from 5% to 95% of sorted array (eliminates outliers)
sarr = sort(spec)
dlim = minmax(spec[sarr[n_elements(sarr)*0.05:n_elements(sarr)*0.95]])
; Set drange with margin factor of 2 on low end and 5 on high end
s.set,drange=dlim*[0.5,5]
loadct,3
s.plot,/log,/xsty,/ysty,ytitle='Frequency [GHz]',charsize=1.5
endif
return,s
end
</pre>
[[File:IDL_TPSP.png|center|500px]]

For synoptic images:
<pre style="background-color: #FCEBD9;">
read_sdo,'eovsa_20191225.spw11-20.tb.disk.fits',header,data,/UNCOMP_DELETE
index2map,header,data,eomap
plot_map,eomap
</pre>

[[File:eovsa_20191225_image_sswidl.jpg| center |250px]]

EOVSA Data Products

2024-03-29T21:07:08Z

Binchen: /* Reading and Using level 1 data */

=Introduction=
EOVSA observes the full disk of the Sun at all times when the Sun is >10 degrees above the local horizon (season dependent and ranges from 7-12 hours duration centered on 20 UT). EOVSA records data at 451 science frequency channels each second, in four polarization products, as well as additional total flux measurements from each individual antenna. Figure 1 summarizes the different levels of data we produce. The later sections will give a more detailed description and usage examples.
[[File:pipeline_flowchart.jpg|center|600px|EOVSA pipeline block diagram/flow chart ]]

=Level 0 - Raw visibility data from the instrument=

As outlined in Figure 1, EOVSA creates raw data products in the left-hand column (labeled Level 0). This includes observations of cosmic sources for phase calibration, and gain and pointing observations required for total power calibration.

==Raw "Interim" Database (IDB) visibility data==
Full-resolution raw "Interim" Database (IDB) visibility data. They are stored in Miriad format, and hence may not be that useful for most people. Be patient after clicking the link--this is a very long list of directories, one for each available date. Recent data (latest few months) can be retrieved from the following page:

https://www.ovsa.njit.edu/fits/IDB/

For older data, visit the UC/Berkeley hosting page:

https://research.ssl.berkeley.edu/data/eovsa/IDB/

==Raw 1-min-averaged visibility data==
This is the same as for the IDB data, except with 1-minute time integration applied. This is typically not useful for flares, but is perfectly fine for imaging active regions and full Sun. These data can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/UDB/

=Level 0.5 - Calibrated visibility data=
After applying calibration and other preliminary processing to the raw (level 0) data, we create the CASA ms’s in the second column in Figure 1 (labeled "level 0.5"). These visibility data are in the Fourier domain of the true images in the plane of the sky and are not immediately ready for spectral imaging analysis yet. However, they have all of the required content to produce images and spectrogram data in standard FITS format (level 1.0). We provide a set of standard ms’s for each day (red boxes in Figure 1), for use by researchers who know how to deal with visibility data. These data are more suitable for experienced users to exploit the full potential of EOVSA data, such as spatially resolved spectral analysis. Processing these data requires CASA or sunCASA (https://github.com/suncasa/suncasa-src). Please refer to our tutorial at [[EOVSA_Data_Analysis_Tutorial]].

==Calibrated full-resolution visibility data for flare events==
Calibrated and self-calibrated visibility data for flare events (purple boxes in Figure 1) will typically be available within 7 days after they are taken. They will be released at our flare list site soon: https://ovsa.njit.edu/flarelist

==Self-calibrated 1-min-averaged visibility data==
EOVSA 1-min averaged visibility data in CASA ms format can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/UDBms_slfcaled

=Level 1.0 - Images and spectrogram data in standard FITS format =

Level 1.0 data are for users who prefer to work with spectrogram (frequency-time) and image data directly, which are also outputs of the pipeline system shown in Figure 1 (orange boxes). They are perfectly suitable to be used as context data for comparison with other multi-wavelength observations but are not (yet) intended for quantitative spatially resolved spectral analysis.

Spectrograms are provided as standard FITS tables containing the frequency list, list of times, and data in both total power (TP) and a sum of amplitudes over intermediate-length baselines (cross power or XP). Likewise, image data products are in FITS format with standard keywords and are converted into the Helioprojective Cartesian coordinate system compatible with the World Coordinate System (WCS) convention, along with correct registration for the spatial, spectral, and temporal coordinates. Both the spectrogram and image data products are calibrated and have physical radio intensity units (sfu for spectrograms and brightness temperature for radio images).

We provide the following level 1 data products:
* Synoptic products:
** '''All-day spectrograms''': Full-day total-power (TP) and cross-power (XP) spectrograms (i.e., no spatial resolution) at full spectral and time resolution in FITS format. One file per day.
** '''All-day synoptic images''': Full disk images at 6 selected frequency bands centered at 1.4, 3.0, 4.5, 6.8, 10.2, and 13.9 GHz are produced once per day utilizing the earth-rotation synthesis, calibrated in brightness temperature. This is because EOVSA has a limited number of baselines and we need a long integration to fill up the uv domain in order to make full-disk images.
* Event-based products:
** '''Flare spectrograms''': These are full time and frequency resolution spectrograms produced from the median of calibrated cross-power visibilities in FITS format, cropped to cover the flare duration. Preflare background is also subtracted. Compared to total-power spectrograms, these spectrograms have the advantage of revealing details of the flare evolution by "filtering out" the large-scale, continuous background from the visibilities. Note that for certain flares that have a large source size, the flux can be lower than its true values (as a fraction of the flux will be "resolved out").
** '''Pipeline-produced spectral images''': We also have a semi-automated flare imaging pipeline to produce calibrated (and self-calibrated) images at 12-s cadence at up to 10 frequency bands. They are saved in standard FITS format and have been registered into Helioprojective coordinates. They can be read by SSWIDL or astropy/sunpy. These data have already been calibrated to physical units and are usually good to be compared with context data. But please be cautious when using them for quantitative spectral analysis.

{| class="wikitable"
|+ Summary of EOVSA Level 1 Data Products
|-
! scope="col"| Category
! scope="col"| Data Product
! scope="col"| Naming Convention
! scope="col"| Download Link
|-
! rowspan="2" | Synoptic Spectrograms
| All-day TP Spectrograms
| EOVSA_TPall_yyyymmdd.fts
!rowspan="9" | https://ovsa.njit.edu/browser
|-
| All-day XP Spectrograms
| EOVSA_XPall_yyyymmdd.fts
|-
! rowspan="7" | Synoptic Images
|-
| Synoptic 1.4 GHz images
| eovsa_yyyymmdd.spw00-01.tb.disk.fits
|-
| Synoptic 3.0 GHz images
| eovsa_yyyymmdd.spw02-05.tb.disk.fits
|-
| Synoptic 4.5 GHz images
| eovsa_yyyymmdd.spw06-10.tb.disk.fits
|-
| Synoptic 6.8 GHz images
| eovsa_yyyymmdd.spw11-20.tb.disk.fits
|-
| Synoptic 10.2 GHz images
| eovsa_yyyymmdd.spw21-30.tb.disk.fits
|-
| Synoptic 13.9 GHz images
| eovsa_yyyymmdd.spw31-43.tb.disk.fits
|-
! rowspan="1" | Flare Spectrograms
| Full-resolution cross-power Spectrogram
| eovsa.spec.flare_id_YYYYMMDDHHMMSS.fits
!rowspan="2" | https://ovsa.njit.edu/flarelist
|-
! rowspan="1" | Flare Spectral Images
| Pipeline-produced spectral images
| eovsa.lev1_mbd_12s.YYYY-MM-DDTHHMMSSZ.image.fits
|-
|}

==Browsing and Downloading level 1 data==
[[File:eovsa_browser.jpg|right|thumb|EOVSA Browser]]
[[file:EOVSA_flarelist.jpg|right|thumb|EOVSA Flare List]]
===Synoptic level 1 data===
EOVSA Level 1 synoptic data products can be retrieved with the following steps:
* Go to [http://ovsa.njit.edu/browser/ EOVSA browser] page.
* Browse to the date of interest.
* Click "synoptic fits" button next to the calendar tool.
* Select the data product based on the names listed in the table above.

===Flare level 1 data===
EOVSA flare list with spectrograms and spectral images can be queried and downloaded at https://ovsa.njit.edu/flarelist. Users can use the top box to select a time range of interest and query our flare list. The results are displayed in the dropdown box. An interactive plot of the flare light curves will be shown at the bottom of the page once an event is highlighted (by clicking on the flare ID). Quicklook plots and FITS files of the spectrograms and flare movies can be accessed by clicking the icons in each flare record.

==Reading and Using level 1 data==
===Introduction===
All our level 1 data products are in FITS format. All the images have standard, WCS-compatible coordinates. Users can use their favorite method to read these files. In the following, we provide minimal examples to read them with Astropy and Sunpy.

===Event-Based Data Products===
* An example of how to read and plot the flare spectrograms and images in Python (with [https://www.astropy.org/ Astropy] and [https://sunpy.org/ SunPy]) can be accessed at [https://colab.research.google.com/drive/1Y3ONWCxLPYvWda5_LqFNxafJtwZDNJBD?usp=sharing#scrollTo=ueiMoHbdxfo- this Google Colab Jupyter notebook].
* We are working on an example with SSWIDL and will post it soon.

===Synoptic Data Products===
* An example of how to read and plot the flare spectrograms and images in Python (with [https://www.astropy.org/ Astropy], [https://sunpy.org/ SunPy], and optionally, [https://docs.sunpy.org/projects/radiospectra/en/latest/ radiospectra]) can be accessed at [https://colab.research.google.com/drive/1Y3ONWCxLPYvWda5_LqFNxafJtwZDNJBD?usp=sharing#scrollTo=IWBHq_Pz0W5- this Google Colab Jupyter notebook].

Additional examples for IDL users. For spectrograms:
<pre style="background-color: #FCEBD9;">
function dspec,filename,doplot=doplot
; Read EOVSA Dynamic Spectrum FITS file <filename> and return a spectrogram object.
; Optionally show an overview plot if doplot switch is set
;
; Usage:
; s = dspec(<filename>) ; Returns spectrogram object
; s = dspec(<filename>,/doplot) ; Plots spectrum and returns spectrogram object
;
; To access the data in the spectrogram object, use
; spec = s.get(/spectrogram) (Array of amplitudes in SFU, of size ntimes, nfreq)
; fghz = s.get(/spectrum_axis) (Array of frequencies in GHz, of size nfreq)
; ut = s.get(/time_axis) (Array of UT times in anytim format, of size ntimes)

default,doplot,0
spec = mrdfits(filename,0)
freq = mrdfits(filename,1)
time = mrdfits(filename,2)
fghz = freq.sfreq
ut = anytim(time)
s = spectrogram(spec,ut,fghz)
if doplot then begin
window,/free,xsiz=1024,ysiz=600
; Find min and max of data from 5% to 95% of sorted array (eliminates outliers)
sarr = sort(spec)
dlim = minmax(spec[sarr[n_elements(sarr)*0.05:n_elements(sarr)*0.95]])
; Set drange with margin factor of 2 on low end and 5 on high end
s.set,drange=dlim*[0.5,5]
loadct,3
s.plot,/log,/xsty,/ysty,ytitle='Frequency [GHz]',charsize=1.5
endif
return,s
end
</pre>
[[File:IDL_TPSP.png|center|500px]]

For synoptic images:
<pre style="background-color: #FCEBD9;">
read_sdo,'eovsa_20191225.spw11-20.tb.disk.fits',header,data,/UNCOMP_DELETE
index2map,header,data,eomap
plot_map,eomap
</pre>

[[File:eovsa_20191225_image_sswidl.jpg| center |250px]]

EOVSA Data Products

2024-03-29T21:05:34Z

Binchen: /* Synoptic Data Products */

=Introduction=
EOVSA observes the full disk of the Sun at all times when the Sun is >10 degrees above the local horizon (season dependent and ranges from 7-12 hours duration centered on 20 UT). EOVSA records data at 451 science frequency channels each second, in four polarization products, as well as additional total flux measurements from each individual antenna. Figure 1 summarizes the different levels of data we produce. The later sections will give a more detailed description and usage examples.
[[File:pipeline_flowchart.jpg|center|600px|EOVSA pipeline block diagram/flow chart ]]

=Level 0 - Raw visibility data from the instrument=

As outlined in Figure 1, EOVSA creates raw data products in the left-hand column (labeled Level 0). This includes observations of cosmic sources for phase calibration, and gain and pointing observations required for total power calibration.

==Raw "Interim" Database (IDB) visibility data==
Full-resolution raw "Interim" Database (IDB) visibility data. They are stored in Miriad format, and hence may not be that useful for most people. Be patient after clicking the link--this is a very long list of directories, one for each available date. Recent data (latest few months) can be retrieved from the following page:

https://www.ovsa.njit.edu/fits/IDB/

For older data, visit the UC/Berkeley hosting page:

https://research.ssl.berkeley.edu/data/eovsa/IDB/

==Raw 1-min-averaged visibility data==
This is the same as for the IDB data, except with 1-minute time integration applied. This is typically not useful for flares, but is perfectly fine for imaging active regions and full Sun. These data can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/UDB/

=Level 0.5 - Calibrated visibility data=
After applying calibration and other preliminary processing to the raw (level 0) data, we create the CASA ms’s in the second column in Figure 1 (labeled "level 0.5"). These visibility data are in the Fourier domain of the true images in the plane of the sky and are not immediately ready for spectral imaging analysis yet. However, they have all of the required content to produce images and spectrogram data in standard FITS format (level 1.0). We provide a set of standard ms’s for each day (red boxes in Figure 1), for use by researchers who know how to deal with visibility data. These data are more suitable for experienced users to exploit the full potential of EOVSA data, such as spatially resolved spectral analysis. Processing these data requires CASA or sunCASA (https://github.com/suncasa/suncasa-src). Please refer to our tutorial at [[EOVSA_Data_Analysis_Tutorial]].

==Calibrated full-resolution visibility data for flare events==
Calibrated and self-calibrated visibility data for flare events (purple boxes in Figure 1) will typically be available within 7 days after they are taken. They will be released at our flare list site soon: https://ovsa.njit.edu/flarelist

==Self-calibrated 1-min-averaged visibility data==
EOVSA 1-min averaged visibility data in CASA ms format can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/UDBms_slfcaled

=Level 1.0 - Images and spectrogram data in standard FITS format =

Level 1.0 data are for users who prefer to work with spectrogram (frequency-time) and image data directly, which are also outputs of the pipeline system shown in Figure 1 (orange boxes). They are perfectly suitable to be used as context data for comparison with other multi-wavelength observations but are not (yet) intended for quantitative spatially resolved spectral analysis.

Spectrograms are provided as standard FITS tables containing the frequency list, list of times, and data in both total power (TP) and a sum of amplitudes over intermediate-length baselines (cross power or XP). Likewise, image data products are in FITS format with standard keywords and are converted into the Helioprojective Cartesian coordinate system compatible with the World Coordinate System (WCS) convention, along with correct registration for the spatial, spectral, and temporal coordinates. Both the spectrogram and image data products are calibrated and have physical radio intensity units (sfu for spectrograms and brightness temperature for radio images).

We provide the following level 1 data products:
* Synoptic products:
** '''All-day spectrograms''': Full-day total-power (TP) and cross-power (XP) spectrograms (i.e., no spatial resolution) at full spectral and time resolution in FITS format. One file per day.
** '''All-day synoptic images''': Full disk images at 6 selected frequency bands centered at 1.4, 3.0, 4.5, 6.8, 10.2, and 13.9 GHz are produced once per day utilizing the earth-rotation synthesis, calibrated in brightness temperature. This is because EOVSA has a limited number of baselines and we need a long integration to fill up the uv domain in order to make full-disk images.
* Event-based products:
** '''Flare spectrograms''': These are full time and frequency resolution spectrograms produced from the median of calibrated cross-power visibilities in FITS format, cropped to cover the flare duration. Preflare background is also subtracted. Compared to total-power spectrograms, these spectrograms have the advantage of revealing details of the flare evolution by "filtering out" the large-scale, continuous background from the visibilities. Note that for certain flares that have a large source size, the flux can be lower than its true values (as a fraction of the flux will be "resolved out").
** '''Pipeline-produced spectral images''': We also have a semi-automated flare imaging pipeline to produce calibrated (and self-calibrated) images at 12-s cadence at up to 10 frequency bands. They are saved in standard FITS format and have been registered into Helioprojective coordinates. They can be read by SSWIDL or astropy/sunpy. These data have already been calibrated to physical units and are usually good to be compared with context data. But please be cautious when using them for quantitative spectral analysis.

{| class="wikitable"
|+ Summary of EOVSA Level 1 Data Products
|-
! scope="col"| Category
! scope="col"| Data Product
! scope="col"| Naming Convention
! scope="col"| Download Link
|-
! rowspan="2" | Synoptic Spectrograms
| All-day TP Spectrograms
| EOVSA_TPall_yyyymmdd.fts
!rowspan="9" | https://ovsa.njit.edu/browser
|-
| All-day XP Spectrograms
| EOVSA_XPall_yyyymmdd.fts
|-
! rowspan="7" | Synoptic Images
|-
| Synoptic 1.4 GHz images
| eovsa_yyyymmdd.spw00-01.tb.disk.fits
|-
| Synoptic 3.0 GHz images
| eovsa_yyyymmdd.spw02-05.tb.disk.fits
|-
| Synoptic 4.5 GHz images
| eovsa_yyyymmdd.spw06-10.tb.disk.fits
|-
| Synoptic 6.8 GHz images
| eovsa_yyyymmdd.spw11-20.tb.disk.fits
|-
| Synoptic 10.2 GHz images
| eovsa_yyyymmdd.spw21-30.tb.disk.fits
|-
| Synoptic 13.9 GHz images
| eovsa_yyyymmdd.spw31-43.tb.disk.fits
|-
! rowspan="1" | Flare Spectrograms
| Full-resolution cross-power Spectrogram
| eovsa.spec.flare_id_YYYYMMDDHHMMSS.fits
!rowspan="2" | https://ovsa.njit.edu/flarelist
|-
! rowspan="1" | Flare Spectral Images
| Pipeline-produced spectral images
| eovsa.lev1_mbd_12s.YYYY-MM-DDTHHMMSSZ.image.fits
|-
|}

==Browsing and Downloading level 1 data==
[[File:eovsa_browser.jpg|right|thumb|EOVSA Browser]]
[[file:EOVSA_flarelist.jpg|right|thumb|EOVSA Flare List]]
===Synoptic level 1 data===
EOVSA Level 1 synoptic data products can be retrieved with the following steps:
* Go to [http://ovsa.njit.edu/browser/ EOVSA browser] page.
* Browse to the date of interest.
* Click "synoptic fits" button next to the calendar tool.
* Select the data product based on the names listed in the table above.

===Flare level 1 data===
EOVSA flare list with spectrograms and spectral images can be queried and downloaded at https://ovsa.njit.edu/flarelist. Users can use the top box to select a time range of interest and query our flare list. The results are displayed in the dropdown box. An interactive plot of the flare light curves will be shown at the bottom of the page once an event is highlighted (by clicking on the flare ID). Quicklook plots and FITS files of the spectrograms and flare movies can be accessed by clicking the icons in each flare record.

==Reading and Using level 1 data==
===Introduction===
All our level 1 data products are in FITS format. All the images have standard, WCS-compatible coordinates. Users can use their favorite method to read these files. In the following, we provide minimal examples to read them with Astropy and Sunpy.

===Event-Based Data Products===
* An example of how to read and plot the flare spectrograms and images in Python (with Astropy and SunPy) can be accessed at [https://colab.research.google.com/drive/1Y3ONWCxLPYvWda5_LqFNxafJtwZDNJBD?usp=sharing#scrollTo=ueiMoHbdxfo- this Google Colab Jupyter notebook].
* We are working on an example with SSWIDL and will post it soon.

===Synoptic Data Products===
* An example of how to read and plot the flare spectrograms and images in Python (with Astropy, SunPy, and optionally, radiospectra) can be accessed at [https://colab.research.google.com/drive/1Y3ONWCxLPYvWda5_LqFNxafJtwZDNJBD?usp=sharing#scrollTo=IWBHq_Pz0W5- this Google Colab Jupyter notebook].

Additional examples for IDL users. For spectrograms:
<pre style="background-color: #FCEBD9;">
function dspec,filename,doplot=doplot
; Read EOVSA Dynamic Spectrum FITS file <filename> and return a spectrogram object.
; Optionally show an overview plot if doplot switch is set
;
; Usage:
; s = dspec(<filename>) ; Returns spectrogram object
; s = dspec(<filename>,/doplot) ; Plots spectrum and returns spectrogram object
;
; To access the data in the spectrogram object, use
; spec = s.get(/spectrogram) (Array of amplitudes in SFU, of size ntimes, nfreq)
; fghz = s.get(/spectrum_axis) (Array of frequencies in GHz, of size nfreq)
; ut = s.get(/time_axis) (Array of UT times in anytim format, of size ntimes)

default,doplot,0
spec = mrdfits(filename,0)
freq = mrdfits(filename,1)
time = mrdfits(filename,2)
fghz = freq.sfreq
ut = anytim(time)
s = spectrogram(spec,ut,fghz)
if doplot then begin
window,/free,xsiz=1024,ysiz=600
; Find min and max of data from 5% to 95% of sorted array (eliminates outliers)
sarr = sort(spec)
dlim = minmax(spec[sarr[n_elements(sarr)*0.05:n_elements(sarr)*0.95]])
; Set drange with margin factor of 2 on low end and 5 on high end
s.set,drange=dlim*[0.5,5]
loadct,3
s.plot,/log,/xsty,/ysty,ytitle='Frequency [GHz]',charsize=1.5
endif
return,s
end
</pre>
[[File:IDL_TPSP.png|center|500px]]

For synoptic images:
<pre style="background-color: #FCEBD9;">
read_sdo,'eovsa_20191225.spw11-20.tb.disk.fits',header,data,/UNCOMP_DELETE
index2map,header,data,eomap
plot_map,eomap
</pre>

[[File:eovsa_20191225_image_sswidl.jpg| center |250px]]

EOVSA Data Products

2024-03-29T21:05:03Z

Binchen: /* Reading and Using level 1 data */

=Introduction=
EOVSA observes the full disk of the Sun at all times when the Sun is >10 degrees above the local horizon (season dependent and ranges from 7-12 hours duration centered on 20 UT). EOVSA records data at 451 science frequency channels each second, in four polarization products, as well as additional total flux measurements from each individual antenna. Figure 1 summarizes the different levels of data we produce. The later sections will give a more detailed description and usage examples.
[[File:pipeline_flowchart.jpg|center|600px|EOVSA pipeline block diagram/flow chart ]]

=Level 0 - Raw visibility data from the instrument=

As outlined in Figure 1, EOVSA creates raw data products in the left-hand column (labeled Level 0). This includes observations of cosmic sources for phase calibration, and gain and pointing observations required for total power calibration.

==Raw "Interim" Database (IDB) visibility data==
Full-resolution raw "Interim" Database (IDB) visibility data. They are stored in Miriad format, and hence may not be that useful for most people. Be patient after clicking the link--this is a very long list of directories, one for each available date. Recent data (latest few months) can be retrieved from the following page:

https://www.ovsa.njit.edu/fits/IDB/

For older data, visit the UC/Berkeley hosting page:

https://research.ssl.berkeley.edu/data/eovsa/IDB/

==Raw 1-min-averaged visibility data==
This is the same as for the IDB data, except with 1-minute time integration applied. This is typically not useful for flares, but is perfectly fine for imaging active regions and full Sun. These data can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/UDB/

=Level 0.5 - Calibrated visibility data=
After applying calibration and other preliminary processing to the raw (level 0) data, we create the CASA ms’s in the second column in Figure 1 (labeled "level 0.5"). These visibility data are in the Fourier domain of the true images in the plane of the sky and are not immediately ready for spectral imaging analysis yet. However, they have all of the required content to produce images and spectrogram data in standard FITS format (level 1.0). We provide a set of standard ms’s for each day (red boxes in Figure 1), for use by researchers who know how to deal with visibility data. These data are more suitable for experienced users to exploit the full potential of EOVSA data, such as spatially resolved spectral analysis. Processing these data requires CASA or sunCASA (https://github.com/suncasa/suncasa-src). Please refer to our tutorial at [[EOVSA_Data_Analysis_Tutorial]].

==Calibrated full-resolution visibility data for flare events==
Calibrated and self-calibrated visibility data for flare events (purple boxes in Figure 1) will typically be available within 7 days after they are taken. They will be released at our flare list site soon: https://ovsa.njit.edu/flarelist

==Self-calibrated 1-min-averaged visibility data==
EOVSA 1-min averaged visibility data in CASA ms format can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/UDBms_slfcaled

=Level 1.0 - Images and spectrogram data in standard FITS format =

Level 1.0 data are for users who prefer to work with spectrogram (frequency-time) and image data directly, which are also outputs of the pipeline system shown in Figure 1 (orange boxes). They are perfectly suitable to be used as context data for comparison with other multi-wavelength observations but are not (yet) intended for quantitative spatially resolved spectral analysis.

Spectrograms are provided as standard FITS tables containing the frequency list, list of times, and data in both total power (TP) and a sum of amplitudes over intermediate-length baselines (cross power or XP). Likewise, image data products are in FITS format with standard keywords and are converted into the Helioprojective Cartesian coordinate system compatible with the World Coordinate System (WCS) convention, along with correct registration for the spatial, spectral, and temporal coordinates. Both the spectrogram and image data products are calibrated and have physical radio intensity units (sfu for spectrograms and brightness temperature for radio images).

We provide the following level 1 data products:
* Synoptic products:
** '''All-day spectrograms''': Full-day total-power (TP) and cross-power (XP) spectrograms (i.e., no spatial resolution) at full spectral and time resolution in FITS format. One file per day.
** '''All-day synoptic images''': Full disk images at 6 selected frequency bands centered at 1.4, 3.0, 4.5, 6.8, 10.2, and 13.9 GHz are produced once per day utilizing the earth-rotation synthesis, calibrated in brightness temperature. This is because EOVSA has a limited number of baselines and we need a long integration to fill up the uv domain in order to make full-disk images.
* Event-based products:
** '''Flare spectrograms''': These are full time and frequency resolution spectrograms produced from the median of calibrated cross-power visibilities in FITS format, cropped to cover the flare duration. Preflare background is also subtracted. Compared to total-power spectrograms, these spectrograms have the advantage of revealing details of the flare evolution by "filtering out" the large-scale, continuous background from the visibilities. Note that for certain flares that have a large source size, the flux can be lower than its true values (as a fraction of the flux will be "resolved out").
** '''Pipeline-produced spectral images''': We also have a semi-automated flare imaging pipeline to produce calibrated (and self-calibrated) images at 12-s cadence at up to 10 frequency bands. They are saved in standard FITS format and have been registered into Helioprojective coordinates. They can be read by SSWIDL or astropy/sunpy. These data have already been calibrated to physical units and are usually good to be compared with context data. But please be cautious when using them for quantitative spectral analysis.

{| class="wikitable"
|+ Summary of EOVSA Level 1 Data Products
|-
! scope="col"| Category
! scope="col"| Data Product
! scope="col"| Naming Convention
! scope="col"| Download Link
|-
! rowspan="2" | Synoptic Spectrograms
| All-day TP Spectrograms
| EOVSA_TPall_yyyymmdd.fts
!rowspan="9" | https://ovsa.njit.edu/browser
|-
| All-day XP Spectrograms
| EOVSA_XPall_yyyymmdd.fts
|-
! rowspan="7" | Synoptic Images
|-
| Synoptic 1.4 GHz images
| eovsa_yyyymmdd.spw00-01.tb.disk.fits
|-
| Synoptic 3.0 GHz images
| eovsa_yyyymmdd.spw02-05.tb.disk.fits
|-
| Synoptic 4.5 GHz images
| eovsa_yyyymmdd.spw06-10.tb.disk.fits
|-
| Synoptic 6.8 GHz images
| eovsa_yyyymmdd.spw11-20.tb.disk.fits
|-
| Synoptic 10.2 GHz images
| eovsa_yyyymmdd.spw21-30.tb.disk.fits
|-
| Synoptic 13.9 GHz images
| eovsa_yyyymmdd.spw31-43.tb.disk.fits
|-
! rowspan="1" | Flare Spectrograms
| Full-resolution cross-power Spectrogram
| eovsa.spec.flare_id_YYYYMMDDHHMMSS.fits
!rowspan="2" | https://ovsa.njit.edu/flarelist
|-
! rowspan="1" | Flare Spectral Images
| Pipeline-produced spectral images
| eovsa.lev1_mbd_12s.YYYY-MM-DDTHHMMSSZ.image.fits
|-
|}

==Browsing and Downloading level 1 data==
[[File:eovsa_browser.jpg|right|thumb|EOVSA Browser]]
[[file:EOVSA_flarelist.jpg|right|thumb|EOVSA Flare List]]
===Synoptic level 1 data===
EOVSA Level 1 synoptic data products can be retrieved with the following steps:
* Go to [http://ovsa.njit.edu/browser/ EOVSA browser] page.
* Browse to the date of interest.
* Click "synoptic fits" button next to the calendar tool.
* Select the data product based on the names listed in the table above.

===Flare level 1 data===
EOVSA flare list with spectrograms and spectral images can be queried and downloaded at https://ovsa.njit.edu/flarelist. Users can use the top box to select a time range of interest and query our flare list. The results are displayed in the dropdown box. An interactive plot of the flare light curves will be shown at the bottom of the page once an event is highlighted (by clicking on the flare ID). Quicklook plots and FITS files of the spectrograms and flare movies can be accessed by clicking the icons in each flare record.

==Reading and Using level 1 data==
===Introduction===
All our level 1 data products are in FITS format. All the images have standard, WCS-compatible coordinates. Users can use their favorite method to read these files. In the following, we provide minimal examples to read them with Astropy and Sunpy.

===Event-Based Data Products===
* An example of how to read and plot the flare spectrograms and images in Python (with Astropy and SunPy) can be accessed at [https://colab.research.google.com/drive/1Y3ONWCxLPYvWda5_LqFNxafJtwZDNJBD?usp=sharing#scrollTo=ueiMoHbdxfo- this Google Colab Jupyter notebook].
* We are working on an example with SSWIDL and will post it soon.

===Synoptic Data Products===
* An example of how to read and plot the flare spectrograms and images in Python (with Astropy and SunPy) can be accessed at [https://colab.research.google.com/drive/1Y3ONWCxLPYvWda5_LqFNxafJtwZDNJBD?usp=sharing#scrollTo=IWBHq_Pz0W5- this Google Colab Jupyter notebook].

Additional examples for IDL users. For spectrograms:
<pre style="background-color: #FCEBD9;">
function dspec,filename,doplot=doplot
; Read EOVSA Dynamic Spectrum FITS file <filename> and return a spectrogram object.
; Optionally show an overview plot if doplot switch is set
;
; Usage:
; s = dspec(<filename>) ; Returns spectrogram object
; s = dspec(<filename>,/doplot) ; Plots spectrum and returns spectrogram object
;
; To access the data in the spectrogram object, use
; spec = s.get(/spectrogram) (Array of amplitudes in SFU, of size ntimes, nfreq)
; fghz = s.get(/spectrum_axis) (Array of frequencies in GHz, of size nfreq)
; ut = s.get(/time_axis) (Array of UT times in anytim format, of size ntimes)

default,doplot,0
spec = mrdfits(filename,0)
freq = mrdfits(filename,1)
time = mrdfits(filename,2)
fghz = freq.sfreq
ut = anytim(time)
s = spectrogram(spec,ut,fghz)
if doplot then begin
window,/free,xsiz=1024,ysiz=600
; Find min and max of data from 5% to 95% of sorted array (eliminates outliers)
sarr = sort(spec)
dlim = minmax(spec[sarr[n_elements(sarr)*0.05:n_elements(sarr)*0.95]])
; Set drange with margin factor of 2 on low end and 5 on high end
s.set,drange=dlim*[0.5,5]
loadct,3
s.plot,/log,/xsty,/ysty,ytitle='Frequency [GHz]',charsize=1.5
endif
return,s
end
</pre>
[[File:IDL_TPSP.png|center|500px]]

For synoptic images:
<pre style="background-color: #FCEBD9;">
read_sdo,'eovsa_20191225.spw11-20.tb.disk.fits',header,data,/UNCOMP_DELETE
index2map,header,data,eomap
plot_map,eomap
</pre>

[[File:eovsa_20191225_image_sswidl.jpg| center |250px]]

OVSA Data Policy

2024-03-29T19:40:12Z

Binchen:

EOVSA data products are open to all scientists and the general public. Although we have an open data policy, the continued availability of EOVSA data relies on the proper acknowledgment of data and personnel support by its users. Guidelines for EOVSA data usage and publication policy are as follows:

=Contacting EOVSA team=
While EOVSA has an open data use policy (i.e., prior permission to access and analyze the data is not required), the data can be subject to limitations that are not immediately evident to users, and at times, the analysis and interpretation of the data involve more in-depth processing. Therefore, we encourage EOVSA data users to contact the EOVSA PIs (Dale Gary and Bin Chen) with a short description of your study and the data products that you intend to use. Contacting the PIs near the start of your project will allow us to:
* Direct you to EOVSA team member(s) who can offer assistance in processing and/or interpreting the data.
* Alert you of any instrumental effects that could possibly result in misinterpretation of EOVSA data products.

We request that EOVSA data users provide the EOVSA PIs with a link to a copy of any papers that include EOVSA data, on submission and again on publication.

=Acknowledgment, Citation, and Authorship=
All publications that use EOVSA data should include a statement in the Acknowledgments section as follows: "'''The Expanded Owens Valley Solar Array (EOVSA) was designed, built, and is now operated by the New Jersey Institute of Technology (NJIT) as a community facility. EOVSA operations are supported by NSF grant AGS-2130832 and NASA grant 80NSSC20K0026 to NJIT.'''" Because these grant numbers change from time to time, please check back to this page for updates.

For all publications that use EOVSA data, authors are asked to:
* Send a link to a copy of the paper to the EOVSA PIs Dale Gary and Bin Chen to keep a record of EOVSA publications.
* Cite the EOVSA first result paper Gary et al. 2018, “Microwave and Hard X-Ray Observations of the 2017 September 10 Solar Limb Flare,” ApJ, 863, 83 ([https://iopscience.iop.org/article/10.3847/1538-4357/aad0ef DOI]; [https://ui.adsabs.harvard.edu/abs/2018ApJ...863...83G/abstract NASA/SAO ADS]). [An EOVSA instrument paper and a pipeline processing paper are being prepared, which will be updated on this page.]

Additionally, for publications that involve more advanced data processing aided by EOVSA team member(s) or use special observing modes:
* Include EOVSA team member(s) in the author list who a) helped process/interpret the data and/or b) helped plan the observations. The authors are encouraged to check with the EOVSA PIs for authorship suggestions.

EOVSA Data Products

2024-03-29T18:43:09Z

Binchen: /* Level 1.0 - Images and spectrogram data in standard FITS format */

=Introduction=
EOVSA observes the full disk of the Sun at all times when the Sun is >10 degrees above the local horizon (season dependent and ranges from 7-12 hours duration centered on 20 UT). EOVSA records data at 451 science frequency channels each second, in four polarization products, as well as additional total flux measurements from each individual antenna. Figure 1 summarizes the different levels of data we produce. The later sections will give a more detailed description and usage examples.
[[File:pipeline_flowchart.jpg|center|600px|EOVSA pipeline block diagram/flow chart ]]

=Level 0 - Raw visibility data from the instrument=

As outlined in Figure 1, EOVSA creates raw data products in the left-hand column (labeled Level 0). This includes observations of cosmic sources for phase calibration, and gain and pointing observations required for total power calibration.

==Raw "Interim" Database (IDB) visibility data==
Full-resolution raw "Interim" Database (IDB) visibility data. They are stored in Miriad format, and hence may not be that useful for most people. Be patient after clicking the link--this is a very long list of directories, one for each available date. Recent data (latest few months) can be retrieved from the following page:

https://www.ovsa.njit.edu/fits/IDB/

For older data, visit the UC/Berkeley hosting page:

https://research.ssl.berkeley.edu/data/eovsa/IDB/

==Raw 1-min-averaged visibility data==
This is the same as for the IDB data, except with 1-minute time integration applied. This is typically not useful for flares, but is perfectly fine for imaging active regions and full Sun. These data can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/UDB/

=Level 0.5 - Calibrated visibility data=
After applying calibration and other preliminary processing to the raw (level 0) data, we create the CASA ms’s in the second column in Figure 1 (labeled "level 0.5"). These visibility data are in the Fourier domain of the true images in the plane of the sky and are not immediately ready for spectral imaging analysis yet. However, they have all of the required content to produce images and spectrogram data in standard FITS format (level 1.0). We provide a set of standard ms’s for each day (red boxes in Figure 1), for use by researchers who know how to deal with visibility data. These data are more suitable for experienced users to exploit the full potential of EOVSA data, such as spatially resolved spectral analysis. Processing these data requires CASA or sunCASA (https://github.com/suncasa/suncasa-src). Please refer to our tutorial at [[EOVSA_Data_Analysis_Tutorial]].

==Calibrated full-resolution visibility data for flare events==
Calibrated and self-calibrated visibility data for flare events (purple boxes in Figure 1) will typically be available within 7 days after they are taken. They will be released at our flare list site soon: https://ovsa.njit.edu/flarelist

==Self-calibrated 1-min-averaged visibility data==
EOVSA 1-min averaged visibility data in CASA ms format can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/UDBms_slfcaled

=Level 1.0 - Images and spectrogram data in standard FITS format =

Level 1.0 data are for users who prefer to work with spectrogram (frequency-time) and image data directly, which are also outputs of the pipeline system shown in Figure 1 (orange boxes). They are perfectly suitable to be used as context data for comparison with other multi-wavelength observations but are not (yet) intended for quantitative spatially resolved spectral analysis.

Spectrograms are provided as standard FITS tables containing the frequency list, list of times, and data in both total power (TP) and a sum of amplitudes over intermediate-length baselines (cross power or XP). Likewise, image data products are in FITS format with standard keywords and are converted into the Helioprojective Cartesian coordinate system compatible with the World Coordinate System (WCS) convention, along with correct registration for the spatial, spectral, and temporal coordinates. Both the spectrogram and image data products are calibrated and have physical radio intensity units (sfu for spectrograms and brightness temperature for radio images).

We provide the following level 1 data products:
* Synoptic products:
** '''All-day spectrograms''': Full-day total-power (TP) and cross-power (XP) spectrograms (i.e., no spatial resolution) at full spectral and time resolution in FITS format. One file per day.
** '''All-day synoptic images''': Full disk images at 6 selected frequency bands centered at 1.4, 3.0, 4.5, 6.8, 10.2, and 13.9 GHz are produced once per day utilizing the earth-rotation synthesis, calibrated in brightness temperature. This is because EOVSA has a limited number of baselines and we need a long integration to fill up the uv domain in order to make full-disk images.
* Event-based products:
** '''Flare spectrograms''': These are full time and frequency resolution spectrograms produced from the median of calibrated cross-power visibilities in FITS format, cropped to cover the flare duration. Preflare background is also subtracted. Compared to total-power spectrograms, these spectrograms have the advantage of revealing details of the flare evolution by "filtering out" the large-scale, continuous background from the visibilities. Note that for certain flares that have a large source size, the flux can be lower than its true values (as a fraction of the flux will be "resolved out").
** '''Pipeline-produced spectral images''': We also have a semi-automated flare imaging pipeline to produce calibrated (and self-calibrated) images at 12-s cadence at up to 10 frequency bands. They are saved in standard FITS format and have been registered into Helioprojective coordinates. They can be read by SSWIDL or astropy/sunpy. These data have already been calibrated to physical units and are usually good to be compared with context data. But please be cautious when using them for quantitative spectral analysis.

{| class="wikitable"
|+ Summary of EOVSA Level 1 Data Products
|-
! scope="col"| Category
! scope="col"| Data Product
! scope="col"| Naming Convention
! scope="col"| Download Link
|-
! rowspan="2" | Synoptic Spectrograms
| All-day TP Spectrograms
| EOVSA_TPall_yyyymmdd.fts
!rowspan="9" | https://ovsa.njit.edu/browser
|-
| All-day XP Spectrograms
| EOVSA_XPall_yyyymmdd.fts
|-
! rowspan="7" | Synoptic Images
|-
| Synoptic 1.4 GHz images
| eovsa_yyyymmdd.spw00-01.tb.disk.fits
|-
| Synoptic 3.0 GHz images
| eovsa_yyyymmdd.spw02-05.tb.disk.fits
|-
| Synoptic 4.5 GHz images
| eovsa_yyyymmdd.spw06-10.tb.disk.fits
|-
| Synoptic 6.8 GHz images
| eovsa_yyyymmdd.spw11-20.tb.disk.fits
|-
| Synoptic 10.2 GHz images
| eovsa_yyyymmdd.spw21-30.tb.disk.fits
|-
| Synoptic 13.9 GHz images
| eovsa_yyyymmdd.spw31-43.tb.disk.fits
|-
! rowspan="1" | Flare Spectrograms
| Full-resolution cross-power Spectrogram
| eovsa.spec.flare_id_YYYYMMDDHHMMSS.fits
!rowspan="2" | https://ovsa.njit.edu/flarelist
|-
! rowspan="1" | Flare Spectral Images
| Pipeline-produced spectral images
| eovsa.lev1_mbd_12s.YYYY-MM-DDTHHMMSSZ.image.fits
|-
|}

==Browsing and Downloading level 1 data==
[[File:eovsa_browser.jpg|right|thumb|EOVSA Browser]]
[[file:EOVSA_flarelist.jpg|right|thumb|EOVSA Flare List]]
===Synoptic level 1 data===
EOVSA Level 1 synoptic data products can be retrieved with the following steps:
* Go to [http://ovsa.njit.edu/browser/ EOVSA browser] page.
* Browse to the date of interest.
* Click "synoptic fits" button next to the calendar tool.
* Select the data product based on the names listed in the table above.

===Flare level 1 data===
EOVSA flare list with spectrograms and spectral images can be queried and downloaded at https://ovsa.njit.edu/flarelist. Users can use the top box to select a time range of interest and query our flare list. The results are displayed in the dropdown box. An interactive plot of the flare light curves will be shown at the bottom of the page once an event is highlighted (by clicking on the flare ID). Quicklook plots and FITS files of the spectrograms and flare movies can be accessed by clicking the icons in each flare record.

==Reading and Using level 1 data==
===Introduction===
All our level 1 data products are in FITS format. All the images have standard, WCS-compatible coordinates. Users can use their favorite method to read these files. In the following, we provide minimal examples to read them with Astropy and Sunpy.

===Event-Based Data Products===
* An example of how to read and plot the flare spectrograms and images in Python (with Astropy and SunPy) can be accessed at [https://colab.research.google.com/drive/1Y3ONWCxLPYvWda5_LqFNxafJtwZDNJBD?usp=sharing#scrollTo=ueiMoHbdxfo- this Google Colab Jupyter notebook].
* We are working on an example with SSWIDL and will post it soon.

===Synoptic Data Products===

====All-day Spectrograms====
To read a spectrogram file in Python using the suncasa library:

<pre style="background-color: #FCEBD9;">
from suncasa.eovsa import eovsa_dspec as ds
from astropy.time import Time
from matplotlib.colors import LogNorm
## Read EOVSA Dynamic Spectrum FITS file <filename>
filename = 'EOVSA_TPall_20170713.fts'
s = ds.get_dspec(filename, doplot=True, cmap='gist_heat', norm=LogNorm(vmax=2.1e3, vmin=40))
## To access the data in the spectrogram object, use
spec = s['spectrogram'] ## (Array of amplitudes in SFU, of size nfreq,ntimes)
fghz = s['spectrum_axis'] ## (Array of frequencies in GHz, of size nfreq)
tim = Time(s['time_axis'], format='mjd') ## (Array of UT times in astropy.time object, of size ntimes)

</pre>

The '''get_dspec''' function is accessible on [https://github.com/suncasa/suncasa-src/blob/master/suncasa/eovsa/eovsa_dspec.py GitHub]. For comprehensive guidance, please refer to suncasa's [https://suncasa-src.readthedocs.io/en/latest/autoapi/suncasa/eovsa/eovsa_dspec/index.html ReadtheDocs page].
[[File:TPSP.jpeg|center|500px]]

The following code will read the spectrogram file in IDL:

<pre style="background-color: #FCEBD9;">
function dspec,filename,doplot=doplot
; Read EOVSA Dynamic Spectrum FITS file <filename> and return a spectrogram object.
; Optionally show an overview plot if doplot switch is set
;
; Usage:
; s = dspec(<filename>) ; Returns spectrogram object
; s = dspec(<filename>,/doplot) ; Plots spectrum and returns spectrogram object
;
; To access the data in the spectrogram object, use
; spec = s.get(/spectrogram) (Array of amplitudes in SFU, of size ntimes, nfreq)
; fghz = s.get(/spectrum_axis) (Array of frequencies in GHz, of size nfreq)
; ut = s.get(/time_axis) (Array of UT times in anytim format, of size ntimes)

default,doplot,0
spec = mrdfits(filename,0)
freq = mrdfits(filename,1)
time = mrdfits(filename,2)
fghz = freq.sfreq
ut = anytim(time)
s = spectrogram(spec,ut,fghz)
if doplot then begin
window,/free,xsiz=1024,ysiz=600
; Find min and max of data from 5% to 95% of sorted array (eliminates outliers)
sarr = sort(spec)
dlim = minmax(spec[sarr[n_elements(sarr)*0.05:n_elements(sarr)*0.95]])
; Set drange with margin factor of 2 on low end and 5 on high end
s.set,drange=dlim*[0.5,5]
loadct,3
s.plot,/log,/xsty,/ysty,ytitle='Frequency [GHz]',charsize=1.5
endif
return,s
end
</pre>
[[File:IDL_TPSP.png|center|500px]]

====Synoptic 6-band Images====
Full disk images at 6 selected frequency bands centered at 1.4, 3.0, 4.5, 6.8, 10.2, and 13.9 GHz are provided once per day, calibrated in brightness temperature. [[File:synoptic_image.jpg| center |400px]]

The EOVSA full disk image FITS files are compressed with the RICE algorithm implemented in the FITS file handling module (astropy.io.fits) in Astropy. EOVSA FITS files are very similar to the compressed SDO/AIA FITS files from JSOC. Popular coding languages can easily read compressed images directly.

In IDL, you can use read_sdo in the ONTOLOGY package, which should be installed by default in SolarSoftWare (SSW), to read compressed EOVSA FITS files. The following code will read the EOVSA image FITS file in SSWIDL:

<pre style="background-color: #FCEBD9;">
read_sdo,'eovsa_20191225.spw11-20.tb.disk.fits',header,data,/UNCOMP_DELETE
index2map,header,data,eomap
plot_map,eomap
</pre>

[[File:eovsa_20191225_image_sswidl.jpg| center |250px]]

In Python, you can use SunPy map module to read EOVAS FITS files. SunPy is an open solar data analysis environment for Python. The installation instruction can be found at [https://sunpy.org/ SunPy official website].
<pre style="background-color: #FCEBD9;">
import matplotlib.pyplot as plt
from sunpy import map as smap
eofile='eovsa_20191225.spw11-20.tb.disk.fits'
eomap = smap.Map(eofile)
eomap.plot()
plt.show()
</pre>
[[File:eovsa_20191225_image_py.jpg| center |250px]]

EOVSA Data Products

2024-03-29T18:42:44Z

Binchen: /* Level 1.0 - Images and spectrogram data in standard FITS format */

=Introduction=
EOVSA observes the full disk of the Sun at all times when the Sun is >10 degrees above the local horizon (season dependent and ranges from 7-12 hours duration centered on 20 UT). EOVSA records data at 451 science frequency channels each second, in four polarization products, as well as additional total flux measurements from each individual antenna. Figure 1 summarizes the different levels of data we produce. The later sections will give a more detailed description and usage examples.
[[File:pipeline_flowchart.jpg|center|600px|EOVSA pipeline block diagram/flow chart ]]

=Level 0 - Raw visibility data from the instrument=

As outlined in Figure 1, EOVSA creates raw data products in the left-hand column (labeled Level 0). This includes observations of cosmic sources for phase calibration, and gain and pointing observations required for total power calibration.

==Raw "Interim" Database (IDB) visibility data==
Full-resolution raw "Interim" Database (IDB) visibility data. They are stored in Miriad format, and hence may not be that useful for most people. Be patient after clicking the link--this is a very long list of directories, one for each available date. Recent data (latest few months) can be retrieved from the following page:

https://www.ovsa.njit.edu/fits/IDB/

For older data, visit the UC/Berkeley hosting page:

https://research.ssl.berkeley.edu/data/eovsa/IDB/

==Raw 1-min-averaged visibility data==
This is the same as for the IDB data, except with 1-minute time integration applied. This is typically not useful for flares, but is perfectly fine for imaging active regions and full Sun. These data can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/UDB/

=Level 0.5 - Calibrated visibility data=
After applying calibration and other preliminary processing to the raw (level 0) data, we create the CASA ms’s in the second column in Figure 1 (labeled "level 0.5"). These visibility data are in the Fourier domain of the true images in the plane of the sky and are not immediately ready for spectral imaging analysis yet. However, they have all of the required content to produce images and spectrogram data in standard FITS format (level 1.0). We provide a set of standard ms’s for each day (red boxes in Figure 1), for use by researchers who know how to deal with visibility data. These data are more suitable for experienced users to exploit the full potential of EOVSA data, such as spatially resolved spectral analysis. Processing these data requires CASA or sunCASA (https://github.com/suncasa/suncasa-src). Please refer to our tutorial at [[EOVSA_Data_Analysis_Tutorial]].

==Calibrated full-resolution visibility data for flare events==
Calibrated and self-calibrated visibility data for flare events (purple boxes in Figure 1) will typically be available within 7 days after they are taken. They will be released at our flare list site soon: https://ovsa.njit.edu/flarelist

==Self-calibrated 1-min-averaged visibility data==
EOVSA 1-min averaged visibility data in CASA ms format can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/UDBms_slfcaled

=Level 1.0 - Images and spectrogram data in standard FITS format =

Level 1.0 data are for users who prefer to work with spectrogram (frequency-time) and image data directly, which are also outputs of the pipeline system shown in Figure 1 (orange boxes). They are perfectly suitable to be used as context data for comparison with other multi-wavelength observations but are not (yet) intended for quantitative spatially resolved spectral analysis.

Spectrograms are provided as standard FITS tables containing the frequency list, list of times, and data in both total power (TP) and a sum of amplitudes over intermediate-length baselines (cross power or XP). Likewise, image data products are in FITS format with standard keywords and are converted into the Helioprojective Cartesian coordinate system compatible with the World Coordinate System (WCS) convention, along with correct registration for the spatial, spectral, and temporal coordinates. Both the spectrogram and image data products are calibrated and have physical radio intensity units (sfu for spectrograms and brightness temperature for radio images).

We provide the following level 1 data products:
* Synoptic products:
** '''All-day spectrograms''': Full-day spectrograms (i.e., no spatial resolution) at full spectral and time resolution in FITS format. One file per day.
** '''All-day synoptic images''': Full disk images at 6 selected frequency bands centered at 1.4, 3.0, 4.5, 6.8, 10.2, and 13.9 GHz are produced once per day utilizing the earth-rotation synthesis, calibrated in brightness temperature. This is because EOVSA has a limited number of baselines and we need a long integration to fill up the uv domain in order to make full-disk images.
* Event-based products:
** '''Flare spectrograms''': These are full time and frequency resolution spectrograms produced from the median of calibrated cross-power visibilities in FITS format, cropped to cover the flare duration. Preflare background is also subtracted. Compared to total-power spectrograms, these spectrograms have the advantage of revealing details of the flare evolution by "filtering out" the large-scale, continuous background from the visibilities. Note that for certain flares that have a large source size, the flux can be lower than its true values (as a fraction of the flux will be "resolved out").
** '''Pipeline-produced spectral images''': We also have a semi-automated flare imaging pipeline to produce calibrated (and self-calibrated) images at 12-s cadence at up to 10 frequency bands. They are saved in standard FITS format and have been registered into Helioprojective coordinates. They can be read by SSWIDL or astropy/sunpy. These data have already been calibrated to physical units and are usually good to be compared with context data. But please be cautious when using them for quantitative spectral analysis.

{| class="wikitable"
|+ Summary of EOVSA Level 1 Data Products
|-
! scope="col"| Category
! scope="col"| Data Product
! scope="col"| Naming Convention
! scope="col"| Download Link
|-
! rowspan="2" | Synoptic Spectrograms
| All-day TP Spectrograms
| EOVSA_TPall_yyyymmdd.fts
!rowspan="9" | https://ovsa.njit.edu/browser
|-
| All-day XP Spectrograms
| EOVSA_XPall_yyyymmdd.fts
|-
! rowspan="7" | Synoptic Images
|-
| Synoptic 1.4 GHz images
| eovsa_yyyymmdd.spw00-01.tb.disk.fits
|-
| Synoptic 3.0 GHz images
| eovsa_yyyymmdd.spw02-05.tb.disk.fits
|-
| Synoptic 4.5 GHz images
| eovsa_yyyymmdd.spw06-10.tb.disk.fits
|-
| Synoptic 6.8 GHz images
| eovsa_yyyymmdd.spw11-20.tb.disk.fits
|-
| Synoptic 10.2 GHz images
| eovsa_yyyymmdd.spw21-30.tb.disk.fits
|-
| Synoptic 13.9 GHz images
| eovsa_yyyymmdd.spw31-43.tb.disk.fits
|-
! rowspan="1" | Flare Spectrograms
| Full-resolution cross-power Spectrogram
| eovsa.spec.flare_id_YYYYMMDDHHMMSS.fits
!rowspan="2" | https://ovsa.njit.edu/flarelist
|-
! rowspan="1" | Flare Spectral Images
| Pipeline-produced spectral images
| eovsa.lev1_mbd_12s.YYYY-MM-DDTHHMMSSZ.image.fits
|-
|}

==Browsing and Downloading level 1 data==
[[File:eovsa_browser.jpg|right|thumb|EOVSA Browser]]
[[file:EOVSA_flarelist.jpg|right|thumb|EOVSA Flare List]]
===Synoptic level 1 data===
EOVSA Level 1 synoptic data products can be retrieved with the following steps:
* Go to [http://ovsa.njit.edu/browser/ EOVSA browser] page.
* Browse to the date of interest.
* Click "synoptic fits" button next to the calendar tool.
* Select the data product based on the names listed in the table above.

===Flare level 1 data===
EOVSA flare list with spectrograms and spectral images can be queried and downloaded at https://ovsa.njit.edu/flarelist. Users can use the top box to select a time range of interest and query our flare list. The results are displayed in the dropdown box. An interactive plot of the flare light curves will be shown at the bottom of the page once an event is highlighted (by clicking on the flare ID). Quicklook plots and FITS files of the spectrograms and flare movies can be accessed by clicking the icons in each flare record.

==Reading and Using level 1 data==
===Introduction===
All our level 1 data products are in FITS format. All the images have standard, WCS-compatible coordinates. Users can use their favorite method to read these files. In the following, we provide minimal examples to read them with Astropy and Sunpy.

===Event-Based Data Products===
* An example of how to read and plot the flare spectrograms and images in Python (with Astropy and SunPy) can be accessed at [https://colab.research.google.com/drive/1Y3ONWCxLPYvWda5_LqFNxafJtwZDNJBD?usp=sharing#scrollTo=ueiMoHbdxfo- this Google Colab Jupyter notebook].
* We are working on an example with SSWIDL and will post it soon.

===Synoptic Data Products===

====All-day Spectrograms====
To read a spectrogram file in Python using the suncasa library:

<pre style="background-color: #FCEBD9;">
from suncasa.eovsa import eovsa_dspec as ds
from astropy.time import Time
from matplotlib.colors import LogNorm
## Read EOVSA Dynamic Spectrum FITS file <filename>
filename = 'EOVSA_TPall_20170713.fts'
s = ds.get_dspec(filename, doplot=True, cmap='gist_heat', norm=LogNorm(vmax=2.1e3, vmin=40))
## To access the data in the spectrogram object, use
spec = s['spectrogram'] ## (Array of amplitudes in SFU, of size nfreq,ntimes)
fghz = s['spectrum_axis'] ## (Array of frequencies in GHz, of size nfreq)
tim = Time(s['time_axis'], format='mjd') ## (Array of UT times in astropy.time object, of size ntimes)

</pre>

The '''get_dspec''' function is accessible on [https://github.com/suncasa/suncasa-src/blob/master/suncasa/eovsa/eovsa_dspec.py GitHub]. For comprehensive guidance, please refer to suncasa's [https://suncasa-src.readthedocs.io/en/latest/autoapi/suncasa/eovsa/eovsa_dspec/index.html ReadtheDocs page].
[[File:TPSP.jpeg|center|500px]]

The following code will read the spectrogram file in IDL:

<pre style="background-color: #FCEBD9;">
function dspec,filename,doplot=doplot
; Read EOVSA Dynamic Spectrum FITS file <filename> and return a spectrogram object.
; Optionally show an overview plot if doplot switch is set
;
; Usage:
; s = dspec(<filename>) ; Returns spectrogram object
; s = dspec(<filename>,/doplot) ; Plots spectrum and returns spectrogram object
;
; To access the data in the spectrogram object, use
; spec = s.get(/spectrogram) (Array of amplitudes in SFU, of size ntimes, nfreq)
; fghz = s.get(/spectrum_axis) (Array of frequencies in GHz, of size nfreq)
; ut = s.get(/time_axis) (Array of UT times in anytim format, of size ntimes)

default,doplot,0
spec = mrdfits(filename,0)
freq = mrdfits(filename,1)
time = mrdfits(filename,2)
fghz = freq.sfreq
ut = anytim(time)
s = spectrogram(spec,ut,fghz)
if doplot then begin
window,/free,xsiz=1024,ysiz=600
; Find min and max of data from 5% to 95% of sorted array (eliminates outliers)
sarr = sort(spec)
dlim = minmax(spec[sarr[n_elements(sarr)*0.05:n_elements(sarr)*0.95]])
; Set drange with margin factor of 2 on low end and 5 on high end
s.set,drange=dlim*[0.5,5]
loadct,3
s.plot,/log,/xsty,/ysty,ytitle='Frequency [GHz]',charsize=1.5
endif
return,s
end
</pre>
[[File:IDL_TPSP.png|center|500px]]

====Synoptic 6-band Images====
Full disk images at 6 selected frequency bands centered at 1.4, 3.0, 4.5, 6.8, 10.2, and 13.9 GHz are provided once per day, calibrated in brightness temperature. [[File:synoptic_image.jpg| center |400px]]

The EOVSA full disk image FITS files are compressed with the RICE algorithm implemented in the FITS file handling module (astropy.io.fits) in Astropy. EOVSA FITS files are very similar to the compressed SDO/AIA FITS files from JSOC. Popular coding languages can easily read compressed images directly.

In IDL, you can use read_sdo in the ONTOLOGY package, which should be installed by default in SolarSoftWare (SSW), to read compressed EOVSA FITS files. The following code will read the EOVSA image FITS file in SSWIDL:

<pre style="background-color: #FCEBD9;">
read_sdo,'eovsa_20191225.spw11-20.tb.disk.fits',header,data,/UNCOMP_DELETE
index2map,header,data,eomap
plot_map,eomap
</pre>

[[File:eovsa_20191225_image_sswidl.jpg| center |250px]]

In Python, you can use SunPy map module to read EOVAS FITS files. SunPy is an open solar data analysis environment for Python. The installation instruction can be found at [https://sunpy.org/ SunPy official website].
<pre style="background-color: #FCEBD9;">
import matplotlib.pyplot as plt
from sunpy import map as smap
eofile='eovsa_20191225.spw11-20.tb.disk.fits'
eomap = smap.Map(eofile)
eomap.plot()
plt.show()
</pre>
[[File:eovsa_20191225_image_py.jpg| center |250px]]

EOVSA Data Products

2024-03-29T18:39:55Z

Binchen: /* Event-Based Data Products */

=Introduction=
EOVSA observes the full disk of the Sun at all times when the Sun is >10 degrees above the local horizon (season dependent and ranges from 7-12 hours duration centered on 20 UT). EOVSA records data at 451 science frequency channels each second, in four polarization products, as well as additional total flux measurements from each individual antenna. Figure 1 summarizes the different levels of data we produce. The later sections will give a more detailed description and usage examples.
[[File:pipeline_flowchart.jpg|center|600px|EOVSA pipeline block diagram/flow chart ]]

=Level 0 - Raw visibility data from the instrument=

As outlined in Figure 1, EOVSA creates raw data products in the left-hand column (labeled Level 0). This includes observations of cosmic sources for phase calibration, and gain and pointing observations required for total power calibration.

==Raw "Interim" Database (IDB) visibility data==
Full-resolution raw "Interim" Database (IDB) visibility data. They are stored in Miriad format, and hence may not be that useful for most people. Be patient after clicking the link--this is a very long list of directories, one for each available date. Recent data (latest few months) can be retrieved from the following page:

https://www.ovsa.njit.edu/fits/IDB/

For older data, visit the UC/Berkeley hosting page:

https://research.ssl.berkeley.edu/data/eovsa/IDB/

==Raw 1-min-averaged visibility data==
This is the same as for the IDB data, except with 1-minute time integration applied. This is typically not useful for flares, but is perfectly fine for imaging active regions and full Sun. These data can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/UDB/

=Level 0.5 - Calibrated visibility data=
After applying calibration and other preliminary processing to the raw (level 0) data, we create the CASA ms’s in the second column in Figure 1 (labeled "level 0.5"). These visibility data are in the Fourier domain of the true images in the plane of the sky and are not immediately ready for spectral imaging analysis yet. However, they have all of the required content to produce images and spectrogram data in standard FITS format (level 1.0). We provide a set of standard ms’s for each day (red boxes in Figure 1), for use by researchers who know how to deal with visibility data. These data are more suitable for experienced users to exploit the full potential of EOVSA data, such as spatially resolved spectral analysis. Processing these data requires CASA or sunCASA (https://github.com/suncasa/suncasa-src). Please refer to our tutorial at [[EOVSA_Data_Analysis_Tutorial]].

==Calibrated full-resolution visibility data for flare events==
Calibrated and self-calibrated visibility data for flare events (purple boxes in Figure 1) will typically be available within 7 days after they are taken. They will be released at our flare list site soon: https://ovsa.njit.edu/flarelist

==Self-calibrated 1-min-averaged visibility data==
EOVSA 1-min averaged visibility data in CASA ms format can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/UDBms_slfcaled

=Level 1.0 - Images and spectrogram data in standard FITS format =

Level 1.0 data are for users who prefer to work with spectrogram (frequency-time) and image data directly, which are also outputs of the pipeline system shown in Figure 1 (orange boxes). They are perfectly suitable to be used as context data for comparison with other multi-wavelength observations but are not (yet) intended for quantitative spatially resolved spectral analysis.

Spectrograms are provided as standard FITS tables containing the frequency list, list of times, and data in both total power (TP) and a sum of amplitudes over intermediate-length baselines (cross power or XP). Likewise, image data products are in FITS format with standard keywords and are converted into the Helioprojective Cartesian coordinate system compatible with the World Coordinate System (WCS) convention, along with correct registration for the spatial, spectral, and temporal coordinates. Both the spectrogram and image data products are calibrated and have physical radio intensity units (sfu for spectrograms and brightness temperature for radio images).

We provide the following level 1 data products:
* Synoptic products:
** '''All-day spectrograms''':
** '''All-day synoptic images''': Full disk images at 6 selected frequency bands centered at 1.4, 3.0, 4.5, 6.8, 10.2, and 13.9 GHz are produced once per day utilizing the earth-rotation synthesis, calibrated in brightness temperature. This is because EOVSA has a limited number of baselines and we need a long integration to fill up the uv domain in order to make full-disk images.
* Event-based products:
** '''Flare spectrograms''': These are full time and frequency resolution spectrograms produced from the median of calibrated cross-power visibilities in FITS format, cropped to cover the flare duration. Preflare background is also subtracted. Compared to total-power spectrograms, these spectrograms have the advantage of revealing details of the flare evolution by "filtering out" the large-scale, continuous background from the visibilities. Note that for certain flares that have a large source size, the flux can be lower than its true values (as a fraction of the flux will be "resolved out").
** '''Pipeline-produced spectral images''': We also have a semi-automated flare imaging pipeline to produce calibrated (and self-calibrated) images at 12-s cadence at up to 10 frequency bands. They are saved in standard FITS format and have been registered into Helioprojective coordinates. They can be read by SSWIDL or astropy/sunpy. These data have already been calibrated to physical units and are usually good to be compared with context data. But please be cautious when using them for quantitative spectral analysis.

{| class="wikitable"
|+ Summary of EOVSA Level 1 Data Products
|-
! scope="col"| Category
! scope="col"| Data Product
! scope="col"| Naming Convention
! scope="col"| Download Link
|-
! rowspan="2" | Synoptic Spectrograms
| All-day TP Spectrograms
| EOVSA_TPall_yyyymmdd.fts
!rowspan="9" | https://ovsa.njit.edu/browser
|-
| All-day XP Spectrograms
| EOVSA_XPall_yyyymmdd.fts
|-
! rowspan="7" | Synoptic Images
|-
| Synoptic 1.4 GHz images
| eovsa_yyyymmdd.spw00-01.tb.disk.fits
|-
| Synoptic 3.0 GHz images
| eovsa_yyyymmdd.spw02-05.tb.disk.fits
|-
| Synoptic 4.5 GHz images
| eovsa_yyyymmdd.spw06-10.tb.disk.fits
|-
| Synoptic 6.8 GHz images
| eovsa_yyyymmdd.spw11-20.tb.disk.fits
|-
| Synoptic 10.2 GHz images
| eovsa_yyyymmdd.spw21-30.tb.disk.fits
|-
| Synoptic 13.9 GHz images
| eovsa_yyyymmdd.spw31-43.tb.disk.fits
|-
! rowspan="1" | Flare Spectrograms
| Full-resolution cross-power Spectrogram
| eovsa.spec.flare_id_YYYYMMDDHHMMSS.fits
!rowspan="2" | https://ovsa.njit.edu/flarelist
|-
! rowspan="1" | Flare Spectral Images
| Pipeline-produced spectral images
| eovsa.lev1_mbd_12s.YYYY-MM-DDTHHMMSSZ.image.fits
|-
|}

==Browsing and Downloading level 1 data==
[[File:eovsa_browser.jpg|right|thumb|EOVSA Browser]]
[[file:EOVSA_flarelist.jpg|right|thumb|EOVSA Flare List]]
===Synoptic level 1 data===
EOVSA Level 1 synoptic data products can be retrieved with the following steps:
* Go to [http://ovsa.njit.edu/browser/ EOVSA browser] page.
* Browse to the date of interest.
* Click "synoptic fits" button next to the calendar tool.
* Select the data product based on the names listed in the table above.

===Flare level 1 data===
EOVSA flare list with spectrograms and spectral images can be queried and downloaded at https://ovsa.njit.edu/flarelist. Users can use the top box to select a time range of interest and query our flare list. The results are displayed in the dropdown box. An interactive plot of the flare light curves will be shown at the bottom of the page once an event is highlighted (by clicking on the flare ID). Quicklook plots and FITS files of the spectrograms and flare movies can be accessed by clicking the icons in each flare record.

==Reading and Using level 1 data==
===Introduction===
All our level 1 data products are in FITS format. All the images have standard, WCS-compatible coordinates. Users can use their favorite method to read these files. In the following, we provide minimal examples to read them with Astropy and Sunpy.

===Event-Based Data Products===
* An example of how to read and plot the flare spectrograms and images in Python (with Astropy and SunPy) can be accessed at [https://colab.research.google.com/drive/1Y3ONWCxLPYvWda5_LqFNxafJtwZDNJBD?usp=sharing#scrollTo=ueiMoHbdxfo- this Google Colab Jupyter notebook].
* We are working on an example with SSWIDL and will post it soon.

===Synoptic Data Products===

====All-day Spectrograms====
To read a spectrogram file in Python using the suncasa library:

<pre style="background-color: #FCEBD9;">
from suncasa.eovsa import eovsa_dspec as ds
from astropy.time import Time
from matplotlib.colors import LogNorm
## Read EOVSA Dynamic Spectrum FITS file <filename>
filename = 'EOVSA_TPall_20170713.fts'
s = ds.get_dspec(filename, doplot=True, cmap='gist_heat', norm=LogNorm(vmax=2.1e3, vmin=40))
## To access the data in the spectrogram object, use
spec = s['spectrogram'] ## (Array of amplitudes in SFU, of size nfreq,ntimes)
fghz = s['spectrum_axis'] ## (Array of frequencies in GHz, of size nfreq)
tim = Time(s['time_axis'], format='mjd') ## (Array of UT times in astropy.time object, of size ntimes)

</pre>

The '''get_dspec''' function is accessible on [https://github.com/suncasa/suncasa-src/blob/master/suncasa/eovsa/eovsa_dspec.py GitHub]. For comprehensive guidance, please refer to suncasa's [https://suncasa-src.readthedocs.io/en/latest/autoapi/suncasa/eovsa/eovsa_dspec/index.html ReadtheDocs page].
[[File:TPSP.jpeg|center|500px]]

The following code will read the spectrogram file in IDL:

<pre style="background-color: #FCEBD9;">
function dspec,filename,doplot=doplot
; Read EOVSA Dynamic Spectrum FITS file <filename> and return a spectrogram object.
; Optionally show an overview plot if doplot switch is set
;
; Usage:
; s = dspec(<filename>) ; Returns spectrogram object
; s = dspec(<filename>,/doplot) ; Plots spectrum and returns spectrogram object
;
; To access the data in the spectrogram object, use
; spec = s.get(/spectrogram) (Array of amplitudes in SFU, of size ntimes, nfreq)
; fghz = s.get(/spectrum_axis) (Array of frequencies in GHz, of size nfreq)
; ut = s.get(/time_axis) (Array of UT times in anytim format, of size ntimes)

default,doplot,0
spec = mrdfits(filename,0)
freq = mrdfits(filename,1)
time = mrdfits(filename,2)
fghz = freq.sfreq
ut = anytim(time)
s = spectrogram(spec,ut,fghz)
if doplot then begin
window,/free,xsiz=1024,ysiz=600
; Find min and max of data from 5% to 95% of sorted array (eliminates outliers)
sarr = sort(spec)
dlim = minmax(spec[sarr[n_elements(sarr)*0.05:n_elements(sarr)*0.95]])
; Set drange with margin factor of 2 on low end and 5 on high end
s.set,drange=dlim*[0.5,5]
loadct,3
s.plot,/log,/xsty,/ysty,ytitle='Frequency [GHz]',charsize=1.5
endif
return,s
end
</pre>
[[File:IDL_TPSP.png|center|500px]]

====Synoptic 6-band Images====
Full disk images at 6 selected frequency bands centered at 1.4, 3.0, 4.5, 6.8, 10.2, and 13.9 GHz are provided once per day, calibrated in brightness temperature. [[File:synoptic_image.jpg| center |400px]]

The EOVSA full disk image FITS files are compressed with the RICE algorithm implemented in the FITS file handling module (astropy.io.fits) in Astropy. EOVSA FITS files are very similar to the compressed SDO/AIA FITS files from JSOC. Popular coding languages can easily read compressed images directly.

In IDL, you can use read_sdo in the ONTOLOGY package, which should be installed by default in SolarSoftWare (SSW), to read compressed EOVSA FITS files. The following code will read the EOVSA image FITS file in SSWIDL:

<pre style="background-color: #FCEBD9;">
read_sdo,'eovsa_20191225.spw11-20.tb.disk.fits',header,data,/UNCOMP_DELETE
index2map,header,data,eomap
plot_map,eomap
</pre>

[[File:eovsa_20191225_image_sswidl.jpg| center |250px]]

In Python, you can use SunPy map module to read EOVAS FITS files. SunPy is an open solar data analysis environment for Python. The installation instruction can be found at [https://sunpy.org/ SunPy official website].
<pre style="background-color: #FCEBD9;">
import matplotlib.pyplot as plt
from sunpy import map as smap
eofile='eovsa_20191225.spw11-20.tb.disk.fits'
eomap = smap.Map(eofile)
eomap.plot()
plt.show()
</pre>
[[File:eovsa_20191225_image_py.jpg| center |250px]]

EOVSA Data Products

2024-03-29T18:11:07Z

Binchen: /* Reading and Using level 1 data */

=Introduction=
EOVSA observes the full disk of the Sun at all times when the Sun is >10 degrees above the local horizon (season dependent and ranges from 7-12 hours duration centered on 20 UT). EOVSA records data at 451 science frequency channels each second, in four polarization products, as well as additional total flux measurements from each individual antenna. Figure 1 summarizes the different levels of data we produce. The later sections will give a more detailed description and usage examples.
[[File:pipeline_flowchart.jpg|center|600px|EOVSA pipeline block diagram/flow chart ]]

=Level 0 - Raw visibility data from the instrument=

As outlined in Figure 1, EOVSA creates raw data products in the left-hand column (labeled Level 0). This includes observations of cosmic sources for phase calibration, and gain and pointing observations required for total power calibration.

==Raw "Interim" Database (IDB) visibility data==
Full-resolution raw "Interim" Database (IDB) visibility data. They are stored in Miriad format, and hence may not be that useful for most people. Be patient after clicking the link--this is a very long list of directories, one for each available date. These data can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/IDB/

==Raw 1-min-averaged visibility data==
This is the same as for the IDB data, except with 1-minute time integration applied. This is typically not useful for flares, but is perfectly fine for imaging active regions and full Sun. These data can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/UDB/

=Level 0.5 - Calibrated visibility data=
After applying calibration and other preliminary processing to the raw (level 0) data, we create the CASA ms’s in the second column in Figure 1 (labeled "level 0.5"). These visibility data are in the Fourier domain of the true images in the plane of the sky and are not immediately ready for spectral imaging analysis yet. However, they have all of the required content to produce images and spectrogram data in standard FITS format (level 1.0). We provide a set of standard ms’s for each day (red boxes in Figure 1), for use by researchers who know how to deal with visibility data. These data are more suitable for experienced users to exploit the full potential of EOVSA data, such as spatially resolved spectral analysis. Processing these data requires CASA or sunCASA (https://github.com/suncasa/suncasa-src). Please refer to our tutorial at [[EOVSA_Data_Analysis_Tutorial]].

==Calibrated full-resolution visibility data for flare events==
Calibrated and self-calibrated visibility data for flare events (purple boxes in Figure 1) will typically be available within 7 days after they are taken. They will be released at our flare list site soon: https://ovsa.njit.edu/flarelist

==Self-calibrated 1-min-averaged visibility data==
EOVSA 1-min averaged visibility data in CASA ms format can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/UDBms_slfcaled

=Level 1.0 - Images and spectrogram data in standard FITS format =

Level 1.0 data are for users who prefer to work with spectrogram (frequency-time) and image data directly, which are also outputs of the pipeline system shown in Figure 1 (orange boxes). They are perfectly suitable to be used as context data for comparison with other multi-wavelength observations but are not (yet) intended for quantitative spatially resolved spectral analysis.

Spectrograms are provided as standard FITS tables containing the frequency list, list of times, and data in both total power (TP) and a sum of amplitudes over intermediate-length baselines (cross power or XP). Likewise, image data products are in FITS format with standard keywords and are converted into the Helioprojective Cartesian coordinate system compatible with the World Coordinate System (WCS) convention, along with correct registration for the spatial, spectral, and temporal coordinates. Both the spectrogram and image data products are calibrated and have physical radio intensity units (sfu for spectrograms and brightness temperature for radio images).

We provide the following level 1 data products:
* Synoptic products:
** '''All-day spectrograms''':
** '''All-day synoptic images''': Full disk images at 6 selected frequency bands centered at 1.4, 3.0, 4.5, 6.8, 10.2, and 13.9 GHz are produced once per day utilizing the earth-rotation synthesis, calibrated in brightness temperature. This is because EOVSA has a limited number of baselines and we need a long integration to fill up the uv domain in order to make full-disk images.
* Event-based products:
** '''Flare spectrograms''': These are full time and frequency resolution spectrograms produced from the median of calibrated cross-power visibilities in FITS format, cropped to cover the flare duration. Preflare background is also subtracted. Compared to total-power spectrograms, these spectrograms have the advantage of revealing details of the flare evolution by "filtering out" the large-scale, continuous background from the visibilities. Note that for certain flares that have a large source size, the flux can be lower than its true values (as a fraction of the flux will be "resolved out").
** '''Pipeline-produced spectral images''': We also have a semi-automated flare imaging pipeline to produce calibrated (and self-calibrated) images at 12-s cadence at up to 10 frequency bands. They are saved in standard FITS format and have been registered into Helioprojective coordinates. They can be read by SSWIDL or astropy/sunpy. These data have already been calibrated to physical units and are usually good to be compared with context data. But please be cautious when using them for quantitative spectral analysis.

{| class="wikitable"
|+ Summary of EOVSA Level 1 Data Products
|-
! scope="col"| Category
! scope="col"| Data Product
! scope="col"| Naming Convention
! scope="col"| Download Link
|-
! rowspan="2" | Synoptic Spectrograms
| All-day TP Spectrograms
| EOVSA_TPall_yyyymmdd.fts
!rowspan="9" | https://ovsa.njit.edu/browser
|-
| All-day XP Spectrograms
| EOVSA_XPall_yyyymmdd.fts
|-
! rowspan="7" | Synoptic Images
|-
| Synoptic 1.4 GHz images
| eovsa_yyyymmdd.spw00-01.tb.disk.fits
|-
| Synoptic 3.0 GHz images
| eovsa_yyyymmdd.spw02-05.tb.disk.fits
|-
| Synoptic 4.5 GHz images
| eovsa_yyyymmdd.spw06-10.tb.disk.fits
|-
| Synoptic 6.8 GHz images
| eovsa_yyyymmdd.spw11-20.tb.disk.fits
|-
| Synoptic 10.2 GHz images
| eovsa_yyyymmdd.spw21-30.tb.disk.fits
|-
| Synoptic 13.9 GHz images
| eovsa_yyyymmdd.spw31-43.tb.disk.fits
|-
! rowspan="1" | Flare Spectrograms
| Full-resolution cross-power Spectrogram
| eovsa.spec.flare_id_YYYYMMDDHHMMSS.fits
!rowspan="2" | https://ovsa.njit.edu/flarelist
|-
! rowspan="1" | Flare Spectral Images
| Pipeline-produced spectral images
| eovsa.lev1_mbd_12s.YYYY-MM-DDTHHMMSSZ.image.fits
|-
|}

==Browsing and Downloading level 1 data==
[[File:eovsa_browser.jpg|right|thumb|EOVSA Browser]]
[[file:EOVSA_flarelist.jpg|right|thumb|EOVSA Flare List]]
===Synoptic level 1 data===
EOVSA Level 1 synoptic data products can be retrieved with the following steps:
* Go to [http://ovsa.njit.edu/browser/ EOVSA browser] page.
* Browse to the date of interest.
* Click "synoptic fits" button next to the calendar tool.
* Select the data product based on the names listed in the table above.

===Flare level 1 data===
EOVSA flare list with spectrograms and spectral images can be queried and downloaded at https://ovsa.njit.edu/flarelist. Users can use the top box to select a time range of interest and query our flare list. The results are displayed in the dropdown box. An interactive plot of the flare light curves will be shown at the bottom of the page once an event is highlighted (by clicking on the flare ID). Quicklook plots and FITS files of the spectrograms and flare movies can be accessed by clicking the icons in each flare record.

==Reading and Using level 1 data==
===Introduction===
All our level 1 data products are in FITS format. All the images have standard, WCS-compatible coordinates. Users can use their favorite method to read these files. In the following, we provide minimal examples to read them with Astropy and Sunpy.

===Event-Based Data Products===
* An example of how to read and plot the flare spectrograms and images in Python (with Astropy and SunPy) can be accessed at [https://colab.research.google.com/drive/1Y3ONWCxLPYvWda5_LqFNxafJtwZDNJBD?usp=sharing#scrollTo=ueiMoHbdxfo- this Google Colab Jupyter notebook].
* We are working on an example with SSWIDL and will release it soon.

===Synoptic Data Products===

====All-day Spectrograms====
To read a spectrogram file in Python using the suncasa library:

<pre style="background-color: #FCEBD9;">
from suncasa.eovsa import eovsa_dspec as ds
from astropy.time import Time
from matplotlib.colors import LogNorm
## Read EOVSA Dynamic Spectrum FITS file <filename>
filename = 'EOVSA_TPall_20170713.fts'
s = ds.get_dspec(filename, doplot=True, cmap='gist_heat', norm=LogNorm(vmax=2.1e3, vmin=40))
## To access the data in the spectrogram object, use
spec = s['spectrogram'] ## (Array of amplitudes in SFU, of size nfreq,ntimes)
fghz = s['spectrum_axis'] ## (Array of frequencies in GHz, of size nfreq)
tim = Time(s['time_axis'], format='mjd') ## (Array of UT times in astropy.time object, of size ntimes)

</pre>

The '''get_dspec''' function is accessible on [https://github.com/suncasa/suncasa-src/blob/master/suncasa/eovsa/eovsa_dspec.py GitHub]. For comprehensive guidance, please refer to suncasa's [https://suncasa-src.readthedocs.io/en/latest/autoapi/suncasa/eovsa/eovsa_dspec/index.html ReadtheDocs page].
[[File:TPSP.jpeg|center|500px]]

The following code will read the spectrogram file in IDL:

<pre style="background-color: #FCEBD9;">
function dspec,filename,doplot=doplot
; Read EOVSA Dynamic Spectrum FITS file <filename> and return a spectrogram object.
; Optionally show an overview plot if doplot switch is set
;
; Usage:
; s = dspec(<filename>) ; Returns spectrogram object
; s = dspec(<filename>,/doplot) ; Plots spectrum and returns spectrogram object
;
; To access the data in the spectrogram object, use
; spec = s.get(/spectrogram) (Array of amplitudes in SFU, of size ntimes, nfreq)
; fghz = s.get(/spectrum_axis) (Array of frequencies in GHz, of size nfreq)
; ut = s.get(/time_axis) (Array of UT times in anytim format, of size ntimes)

default,doplot,0
spec = mrdfits(filename,0)
freq = mrdfits(filename,1)
time = mrdfits(filename,2)
fghz = freq.sfreq
ut = anytim(time)
s = spectrogram(spec,ut,fghz)
if doplot then begin
window,/free,xsiz=1024,ysiz=600
; Find min and max of data from 5% to 95% of sorted array (eliminates outliers)
sarr = sort(spec)
dlim = minmax(spec[sarr[n_elements(sarr)*0.05:n_elements(sarr)*0.95]])
; Set drange with margin factor of 2 on low end and 5 on high end
s.set,drange=dlim*[0.5,5]
loadct,3
s.plot,/log,/xsty,/ysty,ytitle='Frequency [GHz]',charsize=1.5
endif
return,s
end
</pre>
[[File:IDL_TPSP.png|center|500px]]

====Synoptic 6-band Images====
Full disk images at 6 selected frequency bands centered at 1.4, 3.0, 4.5, 6.8, 10.2, and 13.9 GHz are provided once per day, calibrated in brightness temperature. [[File:synoptic_image.jpg| center |400px]]

The EOVSA full disk image FITS files are compressed with the RICE algorithm implemented in the FITS file handling module (astropy.io.fits) in Astropy. EOVSA FITS files are very similar to the compressed SDO/AIA FITS files from JSOC. Popular coding languages can easily read compressed images directly.

In IDL, you can use read_sdo in the ONTOLOGY package, which should be installed by default in SolarSoftWare (SSW), to read compressed EOVSA FITS files. The following code will read the EOVSA image FITS file in SSWIDL:

<pre style="background-color: #FCEBD9;">
read_sdo,'eovsa_20191225.spw11-20.tb.disk.fits',header,data,/UNCOMP_DELETE
index2map,header,data,eomap
plot_map,eomap
</pre>

[[File:eovsa_20191225_image_sswidl.jpg| center |250px]]

In Python, you can use SunPy map module to read EOVAS FITS files. SunPy is an open solar data analysis environment for Python. The installation instruction can be found at [https://sunpy.org/ SunPy official website].
<pre style="background-color: #FCEBD9;">
import matplotlib.pyplot as plt
from sunpy import map as smap
eofile='eovsa_20191225.spw11-20.tb.disk.fits'
eomap = smap.Map(eofile)
eomap.plot()
plt.show()
</pre>
[[File:eovsa_20191225_image_py.jpg| center |250px]]

EOVSA Data Products

2024-03-29T18:10:33Z

Binchen: /* Reading and Using level 1 data */

=Introduction=
EOVSA observes the full disk of the Sun at all times when the Sun is >10 degrees above the local horizon (season dependent and ranges from 7-12 hours duration centered on 20 UT). EOVSA records data at 451 science frequency channels each second, in four polarization products, as well as additional total flux measurements from each individual antenna. Figure 1 summarizes the different levels of data we produce. The later sections will give a more detailed description and usage examples.
[[File:pipeline_flowchart.jpg|center|600px|EOVSA pipeline block diagram/flow chart ]]

=Level 0 - Raw visibility data from the instrument=

As outlined in Figure 1, EOVSA creates raw data products in the left-hand column (labeled Level 0). This includes observations of cosmic sources for phase calibration, and gain and pointing observations required for total power calibration.

==Raw "Interim" Database (IDB) visibility data==
Full-resolution raw "Interim" Database (IDB) visibility data. They are stored in Miriad format, and hence may not be that useful for most people. Be patient after clicking the link--this is a very long list of directories, one for each available date. These data can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/IDB/

==Raw 1-min-averaged visibility data==
This is the same as for the IDB data, except with 1-minute time integration applied. This is typically not useful for flares, but is perfectly fine for imaging active regions and full Sun. These data can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/UDB/

=Level 0.5 - Calibrated visibility data=
After applying calibration and other preliminary processing to the raw (level 0) data, we create the CASA ms’s in the second column in Figure 1 (labeled "level 0.5"). These visibility data are in the Fourier domain of the true images in the plane of the sky and are not immediately ready for spectral imaging analysis yet. However, they have all of the required content to produce images and spectrogram data in standard FITS format (level 1.0). We provide a set of standard ms’s for each day (red boxes in Figure 1), for use by researchers who know how to deal with visibility data. These data are more suitable for experienced users to exploit the full potential of EOVSA data, such as spatially resolved spectral analysis. Processing these data requires CASA or sunCASA (https://github.com/suncasa/suncasa-src). Please refer to our tutorial at [[EOVSA_Data_Analysis_Tutorial]].

==Calibrated full-resolution visibility data for flare events==
Calibrated and self-calibrated visibility data for flare events (purple boxes in Figure 1) will typically be available within 7 days after they are taken. They will be released at our flare list site soon: https://ovsa.njit.edu/flarelist

==Self-calibrated 1-min-averaged visibility data==
EOVSA 1-min averaged visibility data in CASA ms format can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/UDBms_slfcaled

=Level 1.0 - Images and spectrogram data in standard FITS format =

Level 1.0 data are for users who prefer to work with spectrogram (frequency-time) and image data directly, which are also outputs of the pipeline system shown in Figure 1 (orange boxes). They are perfectly suitable to be used as context data for comparison with other multi-wavelength observations but are not (yet) intended for quantitative spatially resolved spectral analysis.

Spectrograms are provided as standard FITS tables containing the frequency list, list of times, and data in both total power (TP) and a sum of amplitudes over intermediate-length baselines (cross power or XP). Likewise, image data products are in FITS format with standard keywords and are converted into the Helioprojective Cartesian coordinate system compatible with the World Coordinate System (WCS) convention, along with correct registration for the spatial, spectral, and temporal coordinates. Both the spectrogram and image data products are calibrated and have physical radio intensity units (sfu for spectrograms and brightness temperature for radio images).

We provide the following level 1 data products:
* Synoptic products:
** '''All-day spectrograms''':
** '''All-day synoptic images''': Full disk images at 6 selected frequency bands centered at 1.4, 3.0, 4.5, 6.8, 10.2, and 13.9 GHz are produced once per day utilizing the earth-rotation synthesis, calibrated in brightness temperature. This is because EOVSA has a limited number of baselines and we need a long integration to fill up the uv domain in order to make full-disk images.
* Event-based products:
** '''Flare spectrograms''': These are full time and frequency resolution spectrograms produced from the median of calibrated cross-power visibilities in FITS format, cropped to cover the flare duration. Preflare background is also subtracted. Compared to total-power spectrograms, these spectrograms have the advantage of revealing details of the flare evolution by "filtering out" the large-scale, continuous background from the visibilities. Note that for certain flares that have a large source size, the flux can be lower than its true values (as a fraction of the flux will be "resolved out").
** '''Pipeline-produced spectral images''': We also have a semi-automated flare imaging pipeline to produce calibrated (and self-calibrated) images at 12-s cadence at up to 10 frequency bands. They are saved in standard FITS format and have been registered into Helioprojective coordinates. They can be read by SSWIDL or astropy/sunpy. These data have already been calibrated to physical units and are usually good to be compared with context data. But please be cautious when using them for quantitative spectral analysis.

{| class="wikitable"
|+ Summary of EOVSA Level 1 Data Products
|-
! scope="col"| Category
! scope="col"| Data Product
! scope="col"| Naming Convention
! scope="col"| Download Link
|-
! rowspan="2" | Synoptic Spectrograms
| All-day TP Spectrograms
| EOVSA_TPall_yyyymmdd.fts
!rowspan="9" | https://ovsa.njit.edu/browser
|-
| All-day XP Spectrograms
| EOVSA_XPall_yyyymmdd.fts
|-
! rowspan="7" | Synoptic Images
|-
| Synoptic 1.4 GHz images
| eovsa_yyyymmdd.spw00-01.tb.disk.fits
|-
| Synoptic 3.0 GHz images
| eovsa_yyyymmdd.spw02-05.tb.disk.fits
|-
| Synoptic 4.5 GHz images
| eovsa_yyyymmdd.spw06-10.tb.disk.fits
|-
| Synoptic 6.8 GHz images
| eovsa_yyyymmdd.spw11-20.tb.disk.fits
|-
| Synoptic 10.2 GHz images
| eovsa_yyyymmdd.spw21-30.tb.disk.fits
|-
| Synoptic 13.9 GHz images
| eovsa_yyyymmdd.spw31-43.tb.disk.fits
|-
! rowspan="1" | Flare Spectrograms
| Full-resolution cross-power Spectrogram
| eovsa.spec.flare_id_YYYYMMDDHHMMSS.fits
!rowspan="2" | https://ovsa.njit.edu/flarelist
|-
! rowspan="1" | Flare Spectral Images
| Pipeline-produced spectral images
| eovsa.lev1_mbd_12s.YYYY-MM-DDTHHMMSSZ.image.fits
|-
|}

==Browsing and Downloading level 1 data==
[[File:eovsa_browser.jpg|right|thumb|EOVSA Browser]]
[[file:EOVSA_flarelist.jpg|right|thumb|EOVSA Flare List]]
===Synoptic level 1 data===
EOVSA Level 1 synoptic data products can be retrieved with the following steps:
* Go to [http://ovsa.njit.edu/browser/ EOVSA browser] page.
* Browse to the date of interest.
* Click "synoptic fits" button next to the calendar tool.
* Select the data product based on the names listed in the table above.

===Flare level 1 data===
EOVSA flare list with spectrograms and spectral images can be queried and downloaded at https://ovsa.njit.edu/flarelist. Users can use the top box to select a time range of interest and query our flare list. The results are displayed in the dropdown box. An interactive plot of the flare light curves will be shown at the bottom of the page once an event is highlighted (by clicking on the flare ID). Quicklook plots and FITS files of the spectrograms and flare movies can be accessed by clicking the icons in each flare record.

==Reading and Using level 1 data==
===Introduction===
All our level 1 data products are in FITS format. All the images have standard, WCS-compatible coordinates. Users can use their favorite method to read these files. In the following, we provide minimal examples to read them with Astropy and Sunpy.

===Event-Based Data Products===
* An example of how to read and plot the flare spectrograms and images in Python (with Astropy and SunPy) can be accessed at [https://colab.research.google.com/drive/1Y3ONWCxLPYvWda5_LqFNxafJtwZDNJBD?usp=sharing#scrollTo=ueiMoHbdxfo- this Google Colab Jupyter notebook].
* We are working on an example with SSWIDL and will release it soon.

===Synoptic Data Products===

====All-day Spectrograms====
To read a spectrogram file in Python using the suncasa library:

<pre style="background-color: #FCEBD9;">
from suncasa.eovsa import eovsa_dspec as ds
from astropy.time import Time
from matplotlib.colors import LogNorm
## Read EOVSA Dynamic Spectrum FITS file <filename>
filename = 'EOVSA_TPall_20170713.fts'
s = ds.get_dspec(filename, doplot=True, cmap='gist_heat', norm=LogNorm(vmax=2.1e3, vmin=40))
## To access the data in the spectrogram object, use
spec = s['spectrogram'] ## (Array of amplitudes in SFU, of size nfreq,ntimes)
fghz = s['spectrum_axis'] ## (Array of frequencies in GHz, of size nfreq)
tim = Time(s['time_axis'], format='mjd') ## (Array of UT times in astropy.time object, of size ntimes)

</pre>

The '''get_dspec''' function is accessible on [https://github.com/suncasa/suncasa-src/blob/master/suncasa/eovsa/eovsa_dspec.py GitHub]. For comprehensive guidance, please refer to suncasa's [https://suncasa-src.readthedocs.io/en/latest/autoapi/suncasa/eovsa/eovsa_dspec/index.html ReadtheDocs page].
[[File:TPSP.jpeg|center|500px]]

The following code will read the spectrogram file in IDL:

<pre style="background-color: #FCEBD9;">
function dspec,filename,doplot=doplot
; Read EOVSA Dynamic Spectrum FITS file <filename> and return a spectrogram object.
; Optionally show an overview plot if doplot switch is set
;
; Usage:
; s = dspec(<filename>) ; Returns spectrogram object
; s = dspec(<filename>,/doplot) ; Plots spectrum and returns spectrogram object
;
; To access the data in the spectrogram object, use
; spec = s.get(/spectrogram) (Array of amplitudes in SFU, of size ntimes, nfreq)
; fghz = s.get(/spectrum_axis) (Array of frequencies in GHz, of size nfreq)
; ut = s.get(/time_axis) (Array of UT times in anytim format, of size ntimes)

default,doplot,0
spec = mrdfits(filename,0)
freq = mrdfits(filename,1)
time = mrdfits(filename,2)
fghz = freq.sfreq
ut = anytim(time)
s = spectrogram(spec,ut,fghz)
if doplot then begin
window,/free,xsiz=1024,ysiz=600
; Find min and max of data from 5% to 95% of sorted array (eliminates outliers)
sarr = sort(spec)
dlim = minmax(spec[sarr[n_elements(sarr)*0.05:n_elements(sarr)*0.95]])
; Set drange with margin factor of 2 on low end and 5 on high end
s.set,drange=dlim*[0.5,5]
loadct,3
s.plot,/log,/xsty,/ysty,ytitle='Frequency [GHz]',charsize=1.5
endif
return,s
end
</pre>
[[File:IDL_TPSP.png|center|500px]]

====Synoptic 6-band Images====
Full disk images at 6 selected frequency bands centered at 1.4, 3.0, 4.5, 6.8, 10.2, and 13.9 GHz are provided once per day, calibrated in brightness temperature. [[File:synoptic_image.jpg| center |400px]]

The EOVSA full disk image FITS files are compressed with the RICE algorithm implemented in the FITS file handling module (astropy.io.fits) in Astropy. EOVSA FITS files are very similar to the compressed SDO/AIA FITS files from JSOC. Popular coding languages can easily read compressed images directly.

In IDL, you can use read_sdo in the ONTOLOGY package, which should be installed by default in SolarSoftWare (SSW), to read compressed EOVSA FITS files. The following code will read the EOVSA image FITS file in SSWIDL:

<pre style="background-color: #FCEBD9;">
read_sdo,'eovsa_20191225.spw11-20.tb.disk.fits',header,data,/UNCOMP_DELETE
index2map,header,data,eomap
plot_map,eomap
</pre>

[[File:eovsa_20191225_image_sswidl.jpg| center |250px]]

In Python, you can use SunPy map module to read EOVAS FITS files. SunPy is an open solar data analysis environment for Python. The installation instruction can be found at [https://sunpy.org/ SunPy official website].
<pre style="background-color: #FCEBD9;">
import matplotlib.pyplot as plt
from sunpy import map as smap
eofile='eovsa_20191225.spw11-20.tb.disk.fits'
eomap = smap.Map(eofile)
eomap.plot()
plt.show()
</pre>
[[File:eovsa_20191225_image_py.jpg| center |250px]]

We have developed a package for EOVSA data processing and analysis:
[https://github.com/suncasa/suncasa SunCASA] A wrapper around [https://casa.nrao.edu/ CASA (the Common Astronomy Software Applications package)] for synthesis imaging and visualizing solar spectral imaging data. CASA is one of the leading software tools for "supporting the data post-processing needs of the next generation of radio astronomical telescopes such as ALMA and VLA", an international effort led by the [https://public.nrao.edu/ National Radio Astronomy Observatory]. The current version of CASA uses Python (2.7) interface. More information about CASA can be found on [https://casa.nrao.edu/ NRAO's CASA website ]. Note, CASA is available ONLY on UNIX-BASED PLATFORMS (and therefore, so is SunCASA). We are developing a new version of SunCASA based on CASA 6 (which offers a modular approach) so that users have the flexibility to build CASA tools and tasks in their Python environment.

Please [http://www.ovsa.njit.edu/wiki/index.php/SunCASA_Installation follow this link] for details regarding the installation of SunCASA on your own machine (only available on Unix-bases OS). This will take you to another page.

OVSA Data Policy

2024-03-29T15:51:09Z

Binchen: Created page with "EOVSA data products are open to all scientists and the general public. Although we have an open data policy, the continued availability of EOVSA data relies on the proper acknowledgment of data and personnel support by its users. Guidelines for EOVSA data usage and publication policy are as follows: =Contacting EOVSA team= While EOVSA has an open data use policy (i.e., prior permission to access and analyze the data is not required), the data can be subject to limitatio..."

EOVSA data products are open to all scientists and the general public. Although we have an open data policy, the continued availability of EOVSA data relies on the proper acknowledgment of data and personnel support by its users. Guidelines for EOVSA data usage and publication policy are as follows:

=Contacting EOVSA team=
While EOVSA has an open data use policy (i.e., prior permission to access and analyze the data is not required), the data can be subject to limitations that are not immediately evident to users, and at times, the analysis and interpretation of the data involve more in-depth processing. Therefore, EOVSA data users should contact the EOVSA PIs (Dale Gary and Bin Chen) with a short description of your study and the data products that you intend to use. Contacting the PIs near the start of your project will allow us to:
* Direct you to EOVSA team member(s) who can offer assistance in processing and/or interpreting the data.
* Alert you of any instrumental effects that could possibly result in misinterpretation of EOVSA data products.

EOVSA data users should provide the EOVSA PIs with a copy of any papers, including EOVSA data, on submission and again on publication.

=Acknowledgment, Citation, and Authorship=
* All publications that use EOVSA data should include a statement in the Acknowledgments section as follows: "'''The Expanded Owens Valley Solar Array (EOVSA) was designed, built, and is now operated by the New Jersey Institute of Technology (NJIT) as a community facility. EOVSA operations are supported by NSF grant AGS-2130832 and NASA grant 80NSSC20K0026 to NJIT.'''"

For all publications that use EOVSA data, authors are asked to:
* Send a copy of the paper to the EOVSA PIs Dale Gary and Bin Chen to keep a record of EOVSA publications.
* Include EOVSA team member(s) in the author list who a) helped process/interpret the data and/or b) helped plan the observations. The authors are encouraged to check with the EOVSA PIs for authorship suggestions.
* Cite the EOVSA first result paper Gary et al. 2018, “Microwave and Hard X-Ray Observations of the 2017 September 10 Solar Limb Flare,” ApJ, 863, 83 ([https://iopscience.iop.org/article/10.3847/1538-4357/aad0ef DOI]; [https://ui.adsabs.harvard.edu/abs/2018ApJ...863...83G/abstract NASA/SAO ADS]). [EOVSA instrument paper and pipeline processing paper are being prepared, which will be updated on this page.]

Owens Valley Solar Arrays

2024-03-29T15:44:37Z

Binchen: /* Using EOVSA Data */

[[File:Eovsa1.png|border|text-top|800px]]

<big>[http://ovsa.njit.edu/ EOVSA] (Expanded Owens Valley Solar Array) is a solar-dedicated radio interferometer operated by the New Jersey Institute of Technology and serving as a '''National Science Foundation Geospace Facility'''. [[File:NSF.jpg|70px]]
<pre>Operation of EOVSA is supported by the National Science Foundation under Grant No. AGS-2130832. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. </pre>
This wiki serves as the site for EOVSA documentation. </big>

[[File:OVRO-LWA1.png|border|text-top|800px]]

<big>OVRO-LWA (Owens Valley Radio Observatory Long Wavelength Array) is an all-sky imager that has a new solar-dedicated spectroscopic imaging mode. OVRO-LWA is a multi-institutional collaboration led by Caltech. NJIT Solar Radio Group is leading its solar-mode development and science. At the bottom of this page are new links for that facility. </big>

== EOVSA Flare List ==

* [https://ovsa.njit.edu/flarelist Query EOVSA Flare list]
* List of EOVSA flares in separate years: [[2024]], [[2023]], [[2022]], [[2021]], [[2020]], [[2019]]

== Using EOVSA Data ==
* <big>[[EOVSA Data products]]</big>: An introduction to standard EOVSA spectrogram and spectral image products with example scripts for reading and plotting.
* <big>[[EOVSA Data Policy]]</big>: Policy for using EOVSA data products.
* <big>Analysis Software</big>: These are for in-depth use of EOVSA data (from calibrated visibilities) and tools for quantitative analysis.
** [https://github.com/suncasa/suncasa SunCASA] A wrapper around [https://casa.nrao.edu/ CASA (the Common Astronomy Software Applications package)] for synthesis imaging and visualizing solar spectral imaging data. CASA is one of the leading software tool for "supporting the data post-processing needs of the next generation of radio astronomical telescopes such as ALMA and VLA", an international effort led by the [https://public.nrao.edu/ National Radio Astronomy Observatory]. The current version of CASA uses Python (2.7) interface. More information about CASA can be found on [https://casa.nrao.edu/ NRAO's CASA website ]. Note, CASA is available ONLY on UNIX-BASED PLATFORMS (and therefore, so is SunCASA).
** [https://github.com/Gelu-Nita/GSFIT GSFIT] A IDL-widget(GUI)-based spectral fitting package called gsfit, which provides a user-friendly display of EOVSA image cubes and an interface to fast fitting codes (via platform-dependent shared-object libraries).
** [https://github.com/suncasa/pygsfit pyGSFIT] A Python-widget(pyQT)-based spectral fitting package, which provides a user-friendly display of EOVSA image cubes, spatially resolved spectra, and an interface to scipy-based fitting codes.
** [[Spectrogram Software]]
** [[Mapping Software]]
* <big>Data Analysis Guides</big>
** <big>[[EOVSA Data Analysis Tutorial 2022]]</big> and <big>[https://colab.research.google.com/drive/19NQb6Emb9HvKX4QHq9ZYCP3RM6nT7sDL#scrollTo=cLdDVptBGG-X EOVSA Workspace]</big> at [https://sphere.boulder.swri.edu/ SPHERE 2022 Workshop]
** <big>[https://colab.research.google.com/drive/1lSLLxgOG6b8kgu9Sk6kSKvrViyubnXG6?usp=sharing#scrollTo=xbXyyLmCFCGL EOVSA Data Analysis Tutorial at RHESSI 19 Workshop]</big>
** <big>[[EOVSA Data Analysis Tutorial]]</big> at [http://rhessi18.umn.edu/ RHESSI XVIII Workshop]
** [[Self-Calibrating Flare Data]] Example script and guides for self-calibrating EOVSA flare data (to be completed)


**[[IDB flare pipeline]] Tutorial to run the flare pipeline for quicklook images



* <big>EOVSA Modeling Guide</big>
**[[GX Simulator]]

* Other helpful links
** [https://casaguides.nrao.edu CASA Guides]
** [http://www.lmsal.com/solarsoft/ SolarSoft IDL]
** [http://www.atnf.csiro.au/computing/software/miriad/userguide/userhtml.html Miriad Guides]
** [https://sites.google.com/site/fgscodes/ Fast Gyrosynchrotron Codes (Alexey Kuznetsov's website)]
** [[Basic GitHub Tutorial]]


* <big>[[Full Disk Simulations]]</big>
* <big>[[All-Day Synthesis Issues]]</big>
* <big>[[Analyzing Pre-2017 Data]]</big>
* <big>[[Fixing Pipeline Problems pre-2021-Feb-07]]</big>

== EOVSA Documentation ==

* <big>General</big>
** [[Downconversion and Frequency Tuning]]
** [[Dealing with Radio Frequency Interference]]
** [[Switching between 200 MHz and 300 MHz Correlator]]
** [[Observing in "Fast" Mode]]

* <big>Computer-Network</big>
** [[Computing Systems]]
** [[Network]]

* <big>Control System</big>
** [[27-m Antenna Commands]]
** [[Schedule Commands]]
** [[Control Commands]]
** [[Attenuation and Level Control]]

* <big>Hardware</big>
** [[Hardware Overview]]
** [[2.1-m Antennas]]
** [[27-m Antennas]]

* <big>System Software</big>
** [[Calibration Database]]
** [[Stateframe Database]]
** [[Database Maintenance]]
** [[Create CASA measurement sets]]

* <big>Calibration</big>
**[[Calibration Overview]]
**[[Pointing Calibration]]
**[[Total Power Calibration]]
**[[System Gain Calibration]]
**[[Antenna Position]] (Baseline Calibration)
**[[Reference Gain Calibration]]
**[[Daily Gain Calibration]]
**[[Delay Calibration]]
**[[Bandpass Calibration]]
**[[Polarization Calibration]]
**[[Calibrator Survey]]
**[[Practical Calibration Tutorial]]

* <big>[[Starburst]]</big>

== System Software ==

* LabVIEW software
* Python code [https://github.com/dgary50/eovsa Github repository]
* [[Python3 Code Installation]]

== EOVSA Observing Log ==
[[2016 November]]; [[2016 December| December]]

[[2017 January]]; [[2017 February | February]]; [[2017 March | March]]; [[2017 April | April]]; [[2017 May | May]]; [[2017 June | June]];
[[2017 July | July]]; [[2017 August | August]]; [[2017 September | September]]; [[2017 October | October]]; [[2017 November | November]]; [[2017 December | December]]

[[2018 January]]; [[2018 February | February]]; [[2018 March | March]]; [[2018 April | April]]; [[2018 May | May]]; [[2018 June | June]];
[[2018 July | July]]; [[2018 August | August]]; [[2018 September | September]]; [[2018 October | October]]; [[2018 November | November]]; [[2018 December | December]]

[[2019 January]]; [[2019 February | February]]; [[2019 March | March]]; [[2019 April | April]]; [[2019 May | May]]; [[2019 June | June]];
[[2019 July | July]]; [[2019 August | August]]; [[2019 September | September]]; [[2019 October | October]]; [[2019 November | November]]; [[2019 December | December]]

[[2020 January]]; [[2020 February | February]]; [[2020 March | March]]; [[2020 April | April]]; [[2020 May | May]]; [[2020 June | June]];
[[2020 July | July]]; [[2020 August | August]]; [[2020 September | September]]; [[2020 October | October]]; [[2020 November | November]]; [[2020 December | December]]

[[2021 January]]; [[2021 February | February]]; [[2021 March | March]]; [[2021 April | April]]; [[2021 May | May]]; [[2021 June | June]];
[[2021 July | July]]; [[2021 August | August]]; [[2021 September | September]]; [[2021 October | October]]; [[2021 November | November]]; [[2021 December | December]]

[[2022 SQL Outage]]

[[2023 January]]; [[2023 February | February]]; [[2023 March | March]]; [[2023 April | April]]; [[2023 May | May]]; [[2023 June | June]];
[[2023 July | July]]; [[2023 August | August]]; [[2023 September | September]]; [[2023 October | October]]; [[2023 November | November]]; [[2023 December | December]]

[[2024 January]]; [[2024 February | February]]; [[2024 March | March]];

== Tohbans ==

[[Trouble Shooting Guide]]

[[Tohban Records]]

[[Owen's Notes]]

[[Caius' Notes]]

[[Tohban EOVSA Imaging Tutorial A-Z]]

[[Tohban OVRO-LWA Imaging Tutorial]]

[[Tohban Guide to Self Calibration and Imaging for EOVSA]]

[[Guide to Upgrade SolarSoft(SSW)]]

== EOVSA Publications ==
Here is a (partial) list of publications that utilize EOVSA data. See also the collection of EOVSA publications at [https://ui.adsabs.harvard.edu/public-libraries/eQ7HfPkySqydu-B8BCt6QQ this NASA/ADS Library].
; 2024
: Collier, H., Hayes, L. A., Yu, S., Battaglia, A. F., Ashfield, W., Polito, V., Harra, L. K., & Krucker, S. (2024), arXiv e-prints, arXiv:2402.10546. [https://ui.adsabs.harvard.edu/abs/2024arXiv240210546C “Localising pulsations in the hard X-ray and microwave emission of an X-class flare”]
: Saqri, J., Veronig, A. M., Battaglia, A. F., Dickson, E. C. M., Gary, D. E., & Krucker, S. (2024), Astronomy and Astrophysics, 683, A41. [https://ui.adsabs.harvard.edu/abs/2024A&A...683A..41S "Efficiency of solar microflares in accelerating electrons when rooted in a sunspot"]
; 2023
: Tan, B., Yan, Y., Huang, J., Zhang, Y., Tan, C., & Zhu, X. (2023), Advances in Space Research, 72, 5563. [https://ui.adsabs.harvard.edu/abs/2023AdSpR..72.5563T "The physics of solar spectral imaging observations in dm-cm wavelengths and the application on space weather"]

: Li, D., Li, Z., Shi, F., Su, Y., Chen, W., Yu, F., Li, C., Qiu, Y., Huang, Y., & Ning, Z. (2023), Astronomy and Astrophysics, 680, L15. [https://ui.adsabs.harvard.edu/abs/2023A&A...680L..15L "Observational signature of continuously operating drivers of decayless kink oscillation"]

: Wang, M., Chen, B., Yu, S., Gary, D. E., Lee, J., Wang, H., & Cohen, C. (2023), The Astrophysical Journal, 954, 32. [https://ui.adsabs.harvard.edu/abs/2023ApJ...954...32W "The Solar Origin of an In Situ Type III Radio Burst Event"]

: Gary, D. E. (2023), Annual Review of Astronomy and Astrophysics, 61, 427. [https://ui.adsabs.harvard.edu/abs/2023ARA&A..61..427G "New Insights from Imaging Spectroscopy of Solar Radio Emission"]

: Nita, G. M., Fleishman, G. D., Kuznetsov, A. A., Anfinogentov, S. A., Stupishin, A. G., Kontar, E. P., Schonfeld, S. J., Klimchuk, J. A., & Gary, D. E. (2023), The Astrophysical Journal Supplement Series, 267, 6. [https://ui.adsabs.harvard.edu/abs/2023ApJS..267....6N "Data-constrained Solar Modeling with GX Simulator"]

: Song, D.-C., Tian, J., Li, Y., Ding, M. D., Su, Y., Yu, S., Hong, J., Qiu, Y., Rao, S., Liu, X., Li, Q., Chen, X., Li, C., & Fang, C. (2023), The Astrophysical Journal, 952, L6. [https://ui.adsabs.harvard.edu/abs/2023ApJ...952L...6S "Spectral Observations and Modeling of a Solar White-light Flare Observed by CHASE"]

: Mondal, S., Chen, B., & Yu, S. (2023), The Astrophysical Journal, 949, 56. [https://ui.adsabs.harvard.edu/abs/2023ApJ...949...56M "Multifrequency Microwave Imaging of Weak Transients from the Quiet Solar Corona"]

: Kontar, E. P., Emslie, A. G., Motorina, G. G., & Dennis, B. R. (2023), The Astrophysical Journal, 947, L13. [https://ui.adsabs.harvard.edu/abs/2023ApJ...947L..13K "The Efficiency of Electron Acceleration during the Impulsive Phase of a Solar Flare"]

: Saqri, J., Veronig, A. M., Dickson, E. C. M., Podladchikova, T., Warmuth, A., Xiao, H., Gary, D. E., Battaglia, A. F., & Krucker, S. (2023), Astronomy and Astrophysics, 672, A23. [https://ui.adsabs.harvard.edu/abs/2023A&A...672A..23S "Multi-point study of the energy release and impulsive CME dynamics in an eruptive C7 flare"]
; 2022

: Kou, Y., Cheng, X., Wang, Y., Yu, S., Chen, B., Kontar, E. P., & Ding, M. (2022), Nature Communications, 13, 7680. [https://ui.adsabs.harvard.edu/abs/2022NatCo..13.7680K "Microwave imaging of quasi-periodic pulsations at flare current sheet"]

: Chertok, I. M. (2022), Monthly Notices of the Royal Astronomical Society, 517, 2709. [https://ui.adsabs.harvard.edu/abs/2022MNRAS.517.2709C "On some features of the solar proton event on 2021 October 28 - GLE73"]

: Lörinčík, J., Polito, V., De Pontieu, B., Yu, S., & Freij, N. (2022), Frontiers in Astronomy and Space Sciences, 9, 334. [https://ui.adsabs.harvard.edu/abs/2022FrASS...940945L "Rapid variations of Si IV spectra in a flare observed by interface region imaging spectrograph at a sub-second cadence"]

: Klein, K.-L., Musset, S., Vilmer, N., Briand, C., Krucker, S., Francesco Battaglia, A., Dresing, N., Palmroos, C., & Gary, D. E. (2022), Astronomy and Astrophysics, 663, A173. [https://ui.adsabs.harvard.edu/abs/2022A&A...663A.173K "The relativistic solar particle event on 28 October 2021: Evidence of particle acceleration within and escape from the solar corona"]

: Fleishman, G. D., Nita, G. M., Chen, B., Yu, S., & Gary, D. E. (2022), Nature, 606, 674. [https://ui.adsabs.harvard.edu/abs/2022Natur.606..674F "Solar flare accelerates nearly all electrons in a large coronal volume"]

: Li, X., Guo, F., Chen, B., Shen, C., & Glesener, L. (2022), The Astrophysical Journal, 932, 92. [https://ui.adsabs.harvard.edu/abs/2022ApJ...932...92L "Modeling Electron Acceleration and Transport in the Early Impulsive Phase of the 2017 September 10th Solar Flare"]

: Zhang, J., Chen, B., Yu, S., Tian, H., Wei, Y., Chen, H., Tan, G., Luo, Y., & Chen, X. (2022), The Astrophysical Journal, 932, 53. [https://ui.adsabs.harvard.edu/abs/2022ApJ...932...53Z "Implications for Additional Plasma Heating Driving the Extreme-ultraviolet Late Phase of a Solar Flare with Microwave Imaging Spectroscopy"]

: Liu, N., Jing, J., Xu, Y., & Wang, H. (2022), The Astrophysical Journal, 930, 154. [https://ui.adsabs.harvard.edu/abs/2022ApJ...930..154L "Multi-instrument Comparative Study of Temperature, Number Density, and Emission Measure during the Precursor Phase of a Solar Flare"]

: López, F. M., Giménez de Castro, C. G., Mandrini, C. H., Simões, P. J. A., Cristiani, G. D., Gary, D. E., Francile, C., & Démoulin, P. (2022), Astronomy and Astrophysics, 657, A51. [https://ui.adsabs.harvard.edu/abs/2022A&A...657A..51L "A solar flare driven by thermal conduction observed in mid-infrared"]

: Unverferth, J., & Longcope, D. (2021), The Astrophysical Journal, 923, 248. [https://ui.adsabs.harvard.edu/abs/2021ApJ...923..248U "Examining Flux Tube Interactions as a Cause of Sub-alfvénic Outflow"]
;2021

: Wei, Y., Chen, B., Yu, S., Wang, H., Jing, J., & Gary, D. E. (2021), The Astrophysical Journal, 923, 213. [https://ui.adsabs.harvard.edu/abs/2021ApJ...923..213W "Coronal Magnetic Field Measurements along a Partially Erupting Filament in a Solar Flare"]

: Jing, J., Inoue, S., Lee, J., Li, Q., Nita, G. M., Xu, Y., Liu, C., Gary, D. E., & Wang, H. (2021), The Astrophysical Journal, 922, 108. [https://ui.adsabs.harvard.edu/abs/2021ApJ...922..108J "Understanding the Initiation of the M2.4 Flare on 2017 July 14"]

: Battaglia, A. F., Saqri, J., Massa, P., Perracchione, E., Dickson, E. C. M., Xiao, H., Veronig, A. M., Warmuth, A., Battaglia, M., Hurford, G. J., Meuris, A., Limousin, O., Etesi, L., Maloney, S. A., Schwartz, R. A., Kuhar, M., Schuller, F., Senthamizh Pavai, V., Musset, S., Ryan, D. F., Kleint, L., Piana, M., Massone, A. M., Benvenuto, F., Sylwester, J., Litwicka, M., Stȩślicki, M., Mrozek, T., Vilmer, N., Fárník, F., Kašparová, J., Mann, G., Gallagher, P. T., Dennis, B. R., Csillaghy, A., Benz, A. O., & Krucker, S. (2021), Astronomy and Astrophysics, 656, A4. [https://ui.adsabs.harvard.edu/abs/2021A&A...656A...4B "STIX X-ray microflare observations during the Solar Orbiter commissioning phase"]

: Shaik, S. B., & Gary, D. E. (2021), The Astrophysical Journal, 919, 44. [https://ui.adsabs.harvard.edu/abs/2021ApJ...919...44S "Implications of Flat Optically Thick Microwave Spectra in Solar Flares for Source Size and Morphology"]

: Kocharov, L., Omodei, N., Mishev, A., Pesce-Rollins, M., Longo, F., Yu, S., Gary, D. E., Vainio, R., & Usoskin, I. (2021), The Astrophysical Journal, 915, 12. [https://ui.adsabs.harvard.edu/abs/2021ApJ...915...12K "Multiple Sources of Solar High-energy Protons"]

: Chen, B., Battaglia, M., Krucker, S., Reeves, K. K., & Glesener, L. (2021), The Astrophysical Journal, 908, L55. [https://ui.adsabs.harvard.edu/abs/2021ApJ...908L..55C "Energetic Electron Distribution of the Coronal Acceleration Region: First Results from Joint Microwave and Hard X-Ray Imaging Spectroscopy"]

: Chhabra, S., Gary, D. E., Hallinan, G., Anderson, M. M., Chen, B., Greenhill, L. J., & Price, D. C. (2021), The Astrophysical Journal, 906, 132. [https://ui.adsabs.harvard.edu/abs/2021ApJ...906..132C "Imaging Spectroscopy of CME-associated Solar Radio Bursts using OVRO-LWA"]
;2020 and earlier

: Reeves, K. K., Polito, V., Chen, B., Galan, G., Yu, S., Liu, W., & Li, G. (2020), The Astrophysical Journal, 905, 165. [https://ui.adsabs.harvard.edu/abs/2020ApJ...905..165R "Hot Plasma Flows and Oscillations in the Loop-top Region During the 2017 September 10 X8.2 Solar Flare"]

: Nindos, A. (2020), Frontiers in Astronomy and Space Sciences, 7, 57. [https://ui.adsabs.harvard.edu/abs/2020FrASS...7...57N "Incoherent Solar Radio Emission"]

: Yu, S., Chen, B., Reeves, K. K., Gary, D. E., Musset, S., Fleishman, G. D., Nita, G. M., & Glesener, L. (2020), The Astrophysical Journal, 900, 17. [https://ui.adsabs.harvard.edu/abs/2020ApJ...900...17Y "Magnetic Reconnection during the Post-impulsive Phase of a Long-duration Solar Flare: Bidirectional Outflows as a Cause of Microwave and X-Ray Bursts"]

: Chen, B., Yu, S., Reeves, K. K., & Gary, D. E. (2020), The Astrophysical Journal, 895, L50. [https://ui.adsabs.harvard.edu/abs/2020ApJ...895L..50C "Microwave Spectral Imaging of an Erupting Magnetic Flux Rope: Implications for the Standard Solar Flare Model in Three Dimensions"]

: Kuroda, N., Fleishman, G. D., Gary, D. E., Nita, G. M., Chen, B., & Yu, S. (2020), Frontiers in Astronomy and Space Sciences, 7, 22. [https://ui.adsabs.harvard.edu/abs/2020FrASS...7...22K "Evolution of Flare-accelerated Electrons Quantified by Spatially Resolved Analysis"]

: Glesener, L., Krucker, S., Duncan, J., Hannah, I. G., Grefenstette, B. W., Chen, B., Smith, D. M., White, S. M., & Hudson, H. (2020), The Astrophysical Journal, 891, L34. [https://ui.adsabs.harvard.edu/abs/2020ApJ...891L..34G "Accelerated Electrons Observed Down to <7 keV in a NuSTAR Solar Microflare"]

: Karlický, M., Chen, B., Gary, D. E., Kašparová, J., & Rybák, J. (2020), The Astrophysical Journal, 889, 72. [https://ui.adsabs.harvard.edu/abs/2020ApJ...889...72K "Drifting Pulsation Structure at the Very Beginning of the 2017 September 10 Limb Flare"]

: Fleishman, G. D., Gary, D. E., Chen, B., Kuroda, N., Yu, S., & Nita, G. M. (2020), Science, 367, 278. [https://ui.adsabs.harvard.edu/abs/2020Sci...367..278F "Decay of the coronal magnetic field can release sufficient energy to power a solar flare"]

: Chen, B., Shen, C., Gary, D. E., Reeves, K. K., Fleishman, G. D., Yu, S., Guo, F., Krucker, S., Lin, J., Nita, G. M., & Kong, X. (2020), Nature Astronomy, 4, 1140. [https://ui.adsabs.harvard.edu/abs/2020NatAs...4.1140C "Measurement of magnetic field and relativistic electrons along a solar flare current sheet"]

: Lee, J. (2018), Journal of Astronomy and Space Sciences, 35, 211. [https://ui.adsabs.harvard.edu/abs/2018JASS...35..211L "Analysis of Solar Microwave Burst Spectrum, I. Nonuniform Magnetic Field"]

: Gary, D. E., Bastian, T. S., Chen, B., Fleishman, G. D., & Glesener, L. (2018), Science with a Next Generation Very Large Array, 517, 99. [https://ui.adsabs.harvard.edu/abs/2018ASPC..517...99G "Radio Observations of Solar Flares"]

: Polito, V., Dudík, J., Kašparová, J., Dzifčáková, E., Reeves, K. K., Testa, P., & Chen, B. (2018), The Astrophysical Journal, 864, 63. [https://ui.adsabs.harvard.edu/abs/2018ApJ...864...63P "Broad Non-Gaussian Fe XXIV Line Profiles in the Impulsive Phase of the 2017 September 10 X8.3-class Flare Observed by Hinode/EIS"]

: Gary, D. E., Chen, B., Dennis, B. R., Fleishman, G. D., Hurford, G. J., Krucker, S., McTiernan, J. M., Nita, G. M., Shih, A. Y., White, S. M., & Yu, S. (2018), The Astrophysical Journal, 863, 83. [https://ui.adsabs.harvard.edu/abs/2018ApJ...863...83G "Microwave and Hard X-Ray Observations of the 2017 September 10 Solar Limb Flare"]

: Fleishman, G. D., Nita, G. M., Kuroda, N., Jia, S., Tong, K., Wen, R. R., & Zhizhuo, Z. (2018), The Astrophysical Journal, 859, 17. [https://ui.adsabs.harvard.edu/abs/2018ApJ...859...17F "Revealing the Evolution of Non-thermal Electrons in Solar Flares Using 3D Modeling"]

: Kuroda, N., Gary, D. E., Wang, H., Fleishman, G. D., Nita, G. M., & Jing, J. (2018), The Astrophysical Journal, 852, 32. [https://ui.adsabs.harvard.edu/abs/2018ApJ...852...32K "Three-dimensional Forward-fit Modeling of the Hard X-Ray and Microwave Emissions of the 2015 June 22 M6.5 Flare"]

: Wang, H., Liu, C., Ahn, K., Xu, Y., Jing, J., Deng, N., Huang, N., Liu, R., Kusano, K., Fleishman, G. D., Gary, D. E., & Cao, W. (2017), Nature Astronomy, 1, 0085. [https://ui.adsabs.harvard.edu/abs/2017NatAs...1E..85W "High-resolution observations of flare precursors in the low solar atmosphere"]

: Nita, G. M., Hickish, J., MacMahon, D., & Gary, D. E. (2016), Journal of Astronomical Instrumentation, 5, 1641009-7366. [https://ui.adsabs.harvard.edu/abs/2016JAI.....541009N "EOVSA Implementation of a Spectral Kurtosis Correlator for Transient Detection and Classification"]

: Nita, G. M., & Gary, D. E. (2016), Journal of Geophysical Research (Space Physics), 121, 7353. [https://ui.adsabs.harvard.edu/abs/2016JGRA..121.7353N "Measurement of duration and signal-to-noise ratio of astronomical transients using a Spectral Kurtosis spectrometer"]

: Wang, Z., Gary, D. E., Fleishman, G. D., & White, S. M. (2015), The Astrophysical Journal, 805, 93. [https://ui.adsabs.harvard.edu/abs/2015ApJ...805...93W "Coronal Magnetography of a Simulated Solar Active Region from Microwave Imaging Spectropolarimetry"]

: Gary, D. E., Fleishman, G. D., & Nita, G. M. (2013), Solar Physics, 288, 549. [https://ui.adsabs.harvard.edu/abs/2013SoPh..288..549G "Magnetography of Solar Flaring Loops with Microwave Imaging Spectropolarimetry"]

== VLA Flare List and Publications ==
See [http://www.ovsa.njit.edu/wiki/index.php/VLA_Data_Survey#List_of_Jansky_VLA_Solar_Observations this link] for a list of flare observations made by the [https://science.nrao.edu/facilities/vla/ Karl G. Jansky Very Large Array] (VLA). Below is a partial list of publications that utilize VLA solar data (see also [https://ui.adsabs.harvard.edu/public-libraries/ZwbjpLo9RS-viufWEoQ95Q this NASA/ADS Library]).
* [https://ui.adsabs.harvard.edu/abs/2022ApJ...940..137L/abstract Luo et al. (2022), ApJ, 940, 137] ''Multiple Regions of Nonthermal Quasiperiodic Pulsations during the Impulsive Phase of a Solar Flare''
* [https://ui.adsabs.harvard.edu/abs/2021ApJ...922..134B/abstract Battaglia et al. (2021), ApJ, 922, 134] ''Multiple Electron Acceleration Instances during a Series of Solar Microflares Observed Simultaneously at X-Rays and Microwaves''
* [https://ui.adsabs.harvard.edu/abs/2021ApJ...911....4L/abstract Luo et al. (2021), ApJ, 911, 4] ''Radio Spectral Imaging of an M8.4 Eruptive Solar Flare: Possible Evidence of a Termination Shock''
* [https://ui.adsabs.harvard.edu/abs/2021ApJ...910...40Z/abstract Zhang et al. (2021), ApJ, 910, 40] ''Multiwavelength Observations of the Formation and Eruption of a Complex Filament''
* [https://ui.adsabs.harvard.edu/abs/2020ApJ...904...94S/abstract Sharma et al. (2020), ApJ, 904, 94] ''Radio and X-Ray Observations of Short-lived Episodes of Electron Acceleration in a Solar Microflare''
* [https://ui.adsabs.harvard.edu/abs/2019ApJ...884...63C/abstract Chen et al. (2019), ApJ, 884, 63] ''Radio Spectroscopic Imaging of a Solar Flare Termination Shock: Split-band Feature as Evidence for Shock Compression''
* [https://ui.adsabs.harvard.edu/abs/2019ApJ...872...71Y/abstract Yu & Chen (2019), ApJ, 872, 71] ''Possible Detection of Subsecond-period Propagating Magnetohydrodynamics Waves in Post-reconnection Magnetic Loops during a Two-ribbon Solar Flare''
* [https://ui.adsabs.harvard.edu/abs/2018ApJ...866...62C/abstract Chen et al. (2018), ApJ, 866, 62] ''Magnetic Reconnection Null Points as the Origin of Semirelativistic Electron Beams in a Solar Jet
''
* [https://ui.adsabs.harvard.edu/abs/2017ApJ...848...77W/abstract Wang et al. (2016), ApJ, 848, 77] ''Dynamic Spectral Imaging of Decimetric Fiber Bursts in an Eruptive Solar Flare''
* [https://ui.adsabs.harvard.edu/abs/2015Sci...350.1238C/abstract Chen et al. (2015), Science, 350, 1238] ''Particle acceleration by a solar flare termination shock''
* [https://ui.adsabs.harvard.edu/abs/2014ApJ...794..149C/abstract Chen et al. (2014), ApJ, 794, 149] ''Direct Evidence of an Eruptive, Filament-hosting Magnetic Flux Rope Leading to a Fast Solar Coronal Mass Ejection''
* [https://ui.adsabs.harvard.edu/abs/2013ApJ...763L..21C/abstract Chen et al. (2013), ApJL, 763, 21] ''Tracing Electron Beams in the Sun's Corona with Radio Dynamic Imaging Spectroscopy''

==Radio Data from Around The Heliosphere==
* [http://ovsa.njit.edu//wiki/index.php/Radio_Data_from_Around_the_World#Radio_Data_Access '' Radio Data '']

=OVRO-LWA Solar-Dedicated Spectroscopic Imager=
The OVRO-LWA (Owens Valley Radio Observatory Long Wavelength Array) has recently been upgraded to include a solar-dedicated beam and two solar imaging modes (slow visibilities of 352 antennas with a 10-s cadence, and fast visibilities of 48 antennas with a 0.1-s cadence). The large collecting area and excellent calibration provide unprecedented high-sensitivity imaging of the quiet Sun and bursts. The array is currently in commissioning and observations are not yet continuous, but they are becoming more so. See the daily realtime data at http://ovsa.njit.edu/status.php for '''real-time display of the spectrogram and a selection of images''', both updated on a 1-min cadence.

==Solar-Dedicated Modes==
===Beamformer===
The beamformer uses the 256 core antennas to form a synthesized beam of more than 1 degree in size that tracks the Sun from sunrise to sunset. This permits a continuous record of the full-Stokes total flux (without spatial resolution) of the Sun (a dynamic spectrum) with 24 kHz frequency resolution (3072 frequencies from 15-90 MHz) and as low as 1 ms time resolution.

===Slow Visibility Imaging===
In this mode, the entire 352-element array is interferometrically correlated to provide visibilities for imaging at all 3072 frequencies at 10-s time resolution. This is ideal for imaging quiet Sun and slowly-varying emission such as coronal mass ejections and active region variability.

===Fast Visibility Imaging===
In this mode, a subset of 48 antennas (chosen to include mainly outer antennas to maintain good spatial resolution) is interferometrically correlated to provide visibilities for imaging at 768 frequencies (96 kHz frequency resolution) at 0.1-s time resolution. This is ideal for imaging rapidly varying emission such as type II and type III bursts as well as many other solar spectral fine structures.

==Inital Data Access==
In its current commissioning state, we try to run the beamformer and imaging pipeline every day in real-time since November 2023 (no latency for beamforming spectrograms and 5-10 min latency for images). Quicklook real-time spectrograms/images can be accessed from http://ovsa.njit.edu/status.php. To access data from previous days, use the following links (replace yyyymmdd with the date you desire):
* Quicklook beamformer total-power spectrograms: http://ovsa.njit.edu/lwa-data/1min_spectra/yyyymmdd/. Check this link for additional daily plots [[Daily OVRO-LWA Beamformer Data]].
* Quicklook multi-frequency movies at 1-min cadence: http://ovsa.njit.edu/lwa-data/1min_images/yyyymmdd/movie_yyyy-mm-dd.html

Note our pipeline processing development is still in the early phase. For example, absolute flux calibrations have not been done for the beamformer spectrograms. Also, artificial effects (including ionospheric refraction effects) are present in the images that cause distortions/shifts. We caution interested users only to consider them for quick-look purposes at this point. Please contact the EOVSA PIs (Dale Gary, Bin Chen) if you intend to use them for science.

== OVRO-LWA Observing Log ==
[https://docs.google.com/document/d/1QDWw5y4HpcE7CSpzXwftMqQT4FDgNJj-6fRrgWrqdug/edit?usp=sharing Link to the OVRO-LWA solar observing logs (in Google Doc)]

Owens Valley Solar Arrays

2024-03-29T15:44:27Z

Binchen: /* Using EOVSA Data */

[[File:Eovsa1.png|border|text-top|800px]]

<big>[http://ovsa.njit.edu/ EOVSA] (Expanded Owens Valley Solar Array) is a solar-dedicated radio interferometer operated by the New Jersey Institute of Technology and serving as a '''National Science Foundation Geospace Facility'''. [[File:NSF.jpg|70px]]
<pre>Operation of EOVSA is supported by the National Science Foundation under Grant No. AGS-2130832. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. </pre>
This wiki serves as the site for EOVSA documentation. </big>

[[File:OVRO-LWA1.png|border|text-top|800px]]

<big>OVRO-LWA (Owens Valley Radio Observatory Long Wavelength Array) is an all-sky imager that has a new solar-dedicated spectroscopic imaging mode. OVRO-LWA is a multi-institutional collaboration led by Caltech. NJIT Solar Radio Group is leading its solar-mode development and science. At the bottom of this page are new links for that facility. </big>

== EOVSA Flare List ==

* [https://ovsa.njit.edu/flarelist Query EOVSA Flare list]
* List of EOVSA flares in separate years: [[2024]], [[2023]], [[2022]], [[2021]], [[2020]], [[2019]]

== Using EOVSA Data ==
* <big>[[EOVSA Data products]]</big>: An introduction to standard EOVSA spectrogram and spectral image products with example scripts for reading and plotting.
* <big>[[EOVSA Data Policy]]</big: Policy for using EOVSA data products.
* <big>Analysis Software</big>: These are for in-depth use of EOVSA data (from calibrated visibilities) and tools for quantitative analysis.
** [https://github.com/suncasa/suncasa SunCASA] A wrapper around [https://casa.nrao.edu/ CASA (the Common Astronomy Software Applications package)] for synthesis imaging and visualizing solar spectral imaging data. CASA is one of the leading software tool for "supporting the data post-processing needs of the next generation of radio astronomical telescopes such as ALMA and VLA", an international effort led by the [https://public.nrao.edu/ National Radio Astronomy Observatory]. The current version of CASA uses Python (2.7) interface. More information about CASA can be found on [https://casa.nrao.edu/ NRAO's CASA website ]. Note, CASA is available ONLY on UNIX-BASED PLATFORMS (and therefore, so is SunCASA).
** [https://github.com/Gelu-Nita/GSFIT GSFIT] A IDL-widget(GUI)-based spectral fitting package called gsfit, which provides a user-friendly display of EOVSA image cubes and an interface to fast fitting codes (via platform-dependent shared-object libraries).
** [https://github.com/suncasa/pygsfit pyGSFIT] A Python-widget(pyQT)-based spectral fitting package, which provides a user-friendly display of EOVSA image cubes, spatially resolved spectra, and an interface to scipy-based fitting codes.
** [[Spectrogram Software]]
** [[Mapping Software]]
* <big>Data Analysis Guides</big>
** <big>[[EOVSA Data Analysis Tutorial 2022]]</big> and <big>[https://colab.research.google.com/drive/19NQb6Emb9HvKX4QHq9ZYCP3RM6nT7sDL#scrollTo=cLdDVptBGG-X EOVSA Workspace]</big> at [https://sphere.boulder.swri.edu/ SPHERE 2022 Workshop]
** <big>[https://colab.research.google.com/drive/1lSLLxgOG6b8kgu9Sk6kSKvrViyubnXG6?usp=sharing#scrollTo=xbXyyLmCFCGL EOVSA Data Analysis Tutorial at RHESSI 19 Workshop]</big>
** <big>[[EOVSA Data Analysis Tutorial]]</big> at [http://rhessi18.umn.edu/ RHESSI XVIII Workshop]
** [[Self-Calibrating Flare Data]] Example script and guides for self-calibrating EOVSA flare data (to be completed)


**[[IDB flare pipeline]] Tutorial to run the flare pipeline for quicklook images



* <big>EOVSA Modeling Guide</big>
**[[GX Simulator]]

* Other helpful links
** [https://casaguides.nrao.edu CASA Guides]
** [http://www.lmsal.com/solarsoft/ SolarSoft IDL]
** [http://www.atnf.csiro.au/computing/software/miriad/userguide/userhtml.html Miriad Guides]
** [https://sites.google.com/site/fgscodes/ Fast Gyrosynchrotron Codes (Alexey Kuznetsov's website)]
** [[Basic GitHub Tutorial]]


* <big>[[Full Disk Simulations]]</big>
* <big>[[All-Day Synthesis Issues]]</big>
* <big>[[Analyzing Pre-2017 Data]]</big>
* <big>[[Fixing Pipeline Problems pre-2021-Feb-07]]</big>

== EOVSA Documentation ==

* <big>General</big>
** [[Downconversion and Frequency Tuning]]
** [[Dealing with Radio Frequency Interference]]
** [[Switching between 200 MHz and 300 MHz Correlator]]
** [[Observing in "Fast" Mode]]

* <big>Computer-Network</big>
** [[Computing Systems]]
** [[Network]]

* <big>Control System</big>
** [[27-m Antenna Commands]]
** [[Schedule Commands]]
** [[Control Commands]]
** [[Attenuation and Level Control]]

* <big>Hardware</big>
** [[Hardware Overview]]
** [[2.1-m Antennas]]
** [[27-m Antennas]]

* <big>System Software</big>
** [[Calibration Database]]
** [[Stateframe Database]]
** [[Database Maintenance]]
** [[Create CASA measurement sets]]

* <big>Calibration</big>
**[[Calibration Overview]]
**[[Pointing Calibration]]
**[[Total Power Calibration]]
**[[System Gain Calibration]]
**[[Antenna Position]] (Baseline Calibration)
**[[Reference Gain Calibration]]
**[[Daily Gain Calibration]]
**[[Delay Calibration]]
**[[Bandpass Calibration]]
**[[Polarization Calibration]]
**[[Calibrator Survey]]
**[[Practical Calibration Tutorial]]

* <big>[[Starburst]]</big>

== System Software ==

* LabVIEW software
* Python code [https://github.com/dgary50/eovsa Github repository]
* [[Python3 Code Installation]]

== EOVSA Observing Log ==
[[2016 November]]; [[2016 December| December]]

[[2017 January]]; [[2017 February | February]]; [[2017 March | March]]; [[2017 April | April]]; [[2017 May | May]]; [[2017 June | June]];
[[2017 July | July]]; [[2017 August | August]]; [[2017 September | September]]; [[2017 October | October]]; [[2017 November | November]]; [[2017 December | December]]

[[2018 January]]; [[2018 February | February]]; [[2018 March | March]]; [[2018 April | April]]; [[2018 May | May]]; [[2018 June | June]];
[[2018 July | July]]; [[2018 August | August]]; [[2018 September | September]]; [[2018 October | October]]; [[2018 November | November]]; [[2018 December | December]]

[[2019 January]]; [[2019 February | February]]; [[2019 March | March]]; [[2019 April | April]]; [[2019 May | May]]; [[2019 June | June]];
[[2019 July | July]]; [[2019 August | August]]; [[2019 September | September]]; [[2019 October | October]]; [[2019 November | November]]; [[2019 December | December]]

[[2020 January]]; [[2020 February | February]]; [[2020 March | March]]; [[2020 April | April]]; [[2020 May | May]]; [[2020 June | June]];
[[2020 July | July]]; [[2020 August | August]]; [[2020 September | September]]; [[2020 October | October]]; [[2020 November | November]]; [[2020 December | December]]

[[2021 January]]; [[2021 February | February]]; [[2021 March | March]]; [[2021 April | April]]; [[2021 May | May]]; [[2021 June | June]];
[[2021 July | July]]; [[2021 August | August]]; [[2021 September | September]]; [[2021 October | October]]; [[2021 November | November]]; [[2021 December | December]]

[[2022 SQL Outage]]

[[2023 January]]; [[2023 February | February]]; [[2023 March | March]]; [[2023 April | April]]; [[2023 May | May]]; [[2023 June | June]];
[[2023 July | July]]; [[2023 August | August]]; [[2023 September | September]]; [[2023 October | October]]; [[2023 November | November]]; [[2023 December | December]]

[[2024 January]]; [[2024 February | February]]; [[2024 March | March]];

== Tohbans ==

[[Trouble Shooting Guide]]

[[Tohban Records]]

[[Owen's Notes]]

[[Caius' Notes]]

[[Tohban EOVSA Imaging Tutorial A-Z]]

[[Tohban OVRO-LWA Imaging Tutorial]]

[[Tohban Guide to Self Calibration and Imaging for EOVSA]]

[[Guide to Upgrade SolarSoft(SSW)]]

== EOVSA Publications ==
Here is a (partial) list of publications that utilize EOVSA data. See also the collection of EOVSA publications at [https://ui.adsabs.harvard.edu/public-libraries/eQ7HfPkySqydu-B8BCt6QQ this NASA/ADS Library].
; 2024
: Collier, H., Hayes, L. A., Yu, S., Battaglia, A. F., Ashfield, W., Polito, V., Harra, L. K., & Krucker, S. (2024), arXiv e-prints, arXiv:2402.10546. [https://ui.adsabs.harvard.edu/abs/2024arXiv240210546C “Localising pulsations in the hard X-ray and microwave emission of an X-class flare”]
: Saqri, J., Veronig, A. M., Battaglia, A. F., Dickson, E. C. M., Gary, D. E., & Krucker, S. (2024), Astronomy and Astrophysics, 683, A41. [https://ui.adsabs.harvard.edu/abs/2024A&A...683A..41S "Efficiency of solar microflares in accelerating electrons when rooted in a sunspot"]
; 2023
: Tan, B., Yan, Y., Huang, J., Zhang, Y., Tan, C., & Zhu, X. (2023), Advances in Space Research, 72, 5563. [https://ui.adsabs.harvard.edu/abs/2023AdSpR..72.5563T "The physics of solar spectral imaging observations in dm-cm wavelengths and the application on space weather"]

: Li, D., Li, Z., Shi, F., Su, Y., Chen, W., Yu, F., Li, C., Qiu, Y., Huang, Y., & Ning, Z. (2023), Astronomy and Astrophysics, 680, L15. [https://ui.adsabs.harvard.edu/abs/2023A&A...680L..15L "Observational signature of continuously operating drivers of decayless kink oscillation"]

: Wang, M., Chen, B., Yu, S., Gary, D. E., Lee, J., Wang, H., & Cohen, C. (2023), The Astrophysical Journal, 954, 32. [https://ui.adsabs.harvard.edu/abs/2023ApJ...954...32W "The Solar Origin of an In Situ Type III Radio Burst Event"]

: Gary, D. E. (2023), Annual Review of Astronomy and Astrophysics, 61, 427. [https://ui.adsabs.harvard.edu/abs/2023ARA&A..61..427G "New Insights from Imaging Spectroscopy of Solar Radio Emission"]

: Nita, G. M., Fleishman, G. D., Kuznetsov, A. A., Anfinogentov, S. A., Stupishin, A. G., Kontar, E. P., Schonfeld, S. J., Klimchuk, J. A., & Gary, D. E. (2023), The Astrophysical Journal Supplement Series, 267, 6. [https://ui.adsabs.harvard.edu/abs/2023ApJS..267....6N "Data-constrained Solar Modeling with GX Simulator"]

: Song, D.-C., Tian, J., Li, Y., Ding, M. D., Su, Y., Yu, S., Hong, J., Qiu, Y., Rao, S., Liu, X., Li, Q., Chen, X., Li, C., & Fang, C. (2023), The Astrophysical Journal, 952, L6. [https://ui.adsabs.harvard.edu/abs/2023ApJ...952L...6S "Spectral Observations and Modeling of a Solar White-light Flare Observed by CHASE"]

: Mondal, S., Chen, B., & Yu, S. (2023), The Astrophysical Journal, 949, 56. [https://ui.adsabs.harvard.edu/abs/2023ApJ...949...56M "Multifrequency Microwave Imaging of Weak Transients from the Quiet Solar Corona"]

: Kontar, E. P., Emslie, A. G., Motorina, G. G., & Dennis, B. R. (2023), The Astrophysical Journal, 947, L13. [https://ui.adsabs.harvard.edu/abs/2023ApJ...947L..13K "The Efficiency of Electron Acceleration during the Impulsive Phase of a Solar Flare"]

: Saqri, J., Veronig, A. M., Dickson, E. C. M., Podladchikova, T., Warmuth, A., Xiao, H., Gary, D. E., Battaglia, A. F., & Krucker, S. (2023), Astronomy and Astrophysics, 672, A23. [https://ui.adsabs.harvard.edu/abs/2023A&A...672A..23S "Multi-point study of the energy release and impulsive CME dynamics in an eruptive C7 flare"]
; 2022

: Kou, Y., Cheng, X., Wang, Y., Yu, S., Chen, B., Kontar, E. P., & Ding, M. (2022), Nature Communications, 13, 7680. [https://ui.adsabs.harvard.edu/abs/2022NatCo..13.7680K "Microwave imaging of quasi-periodic pulsations at flare current sheet"]

: Chertok, I. M. (2022), Monthly Notices of the Royal Astronomical Society, 517, 2709. [https://ui.adsabs.harvard.edu/abs/2022MNRAS.517.2709C "On some features of the solar proton event on 2021 October 28 - GLE73"]

: Lörinčík, J., Polito, V., De Pontieu, B., Yu, S., & Freij, N. (2022), Frontiers in Astronomy and Space Sciences, 9, 334. [https://ui.adsabs.harvard.edu/abs/2022FrASS...940945L "Rapid variations of Si IV spectra in a flare observed by interface region imaging spectrograph at a sub-second cadence"]

: Klein, K.-L., Musset, S., Vilmer, N., Briand, C., Krucker, S., Francesco Battaglia, A., Dresing, N., Palmroos, C., & Gary, D. E. (2022), Astronomy and Astrophysics, 663, A173. [https://ui.adsabs.harvard.edu/abs/2022A&A...663A.173K "The relativistic solar particle event on 28 October 2021: Evidence of particle acceleration within and escape from the solar corona"]

: Fleishman, G. D., Nita, G. M., Chen, B., Yu, S., & Gary, D. E. (2022), Nature, 606, 674. [https://ui.adsabs.harvard.edu/abs/2022Natur.606..674F "Solar flare accelerates nearly all electrons in a large coronal volume"]

: Li, X., Guo, F., Chen, B., Shen, C., & Glesener, L. (2022), The Astrophysical Journal, 932, 92. [https://ui.adsabs.harvard.edu/abs/2022ApJ...932...92L "Modeling Electron Acceleration and Transport in the Early Impulsive Phase of the 2017 September 10th Solar Flare"]

: Zhang, J., Chen, B., Yu, S., Tian, H., Wei, Y., Chen, H., Tan, G., Luo, Y., & Chen, X. (2022), The Astrophysical Journal, 932, 53. [https://ui.adsabs.harvard.edu/abs/2022ApJ...932...53Z "Implications for Additional Plasma Heating Driving the Extreme-ultraviolet Late Phase of a Solar Flare with Microwave Imaging Spectroscopy"]

: Liu, N., Jing, J., Xu, Y., & Wang, H. (2022), The Astrophysical Journal, 930, 154. [https://ui.adsabs.harvard.edu/abs/2022ApJ...930..154L "Multi-instrument Comparative Study of Temperature, Number Density, and Emission Measure during the Precursor Phase of a Solar Flare"]

: López, F. M., Giménez de Castro, C. G., Mandrini, C. H., Simões, P. J. A., Cristiani, G. D., Gary, D. E., Francile, C., & Démoulin, P. (2022), Astronomy and Astrophysics, 657, A51. [https://ui.adsabs.harvard.edu/abs/2022A&A...657A..51L "A solar flare driven by thermal conduction observed in mid-infrared"]

: Unverferth, J., & Longcope, D. (2021), The Astrophysical Journal, 923, 248. [https://ui.adsabs.harvard.edu/abs/2021ApJ...923..248U "Examining Flux Tube Interactions as a Cause of Sub-alfvénic Outflow"]
;2021

: Wei, Y., Chen, B., Yu, S., Wang, H., Jing, J., & Gary, D. E. (2021), The Astrophysical Journal, 923, 213. [https://ui.adsabs.harvard.edu/abs/2021ApJ...923..213W "Coronal Magnetic Field Measurements along a Partially Erupting Filament in a Solar Flare"]

: Jing, J., Inoue, S., Lee, J., Li, Q., Nita, G. M., Xu, Y., Liu, C., Gary, D. E., & Wang, H. (2021), The Astrophysical Journal, 922, 108. [https://ui.adsabs.harvard.edu/abs/2021ApJ...922..108J "Understanding the Initiation of the M2.4 Flare on 2017 July 14"]

: Battaglia, A. F., Saqri, J., Massa, P., Perracchione, E., Dickson, E. C. M., Xiao, H., Veronig, A. M., Warmuth, A., Battaglia, M., Hurford, G. J., Meuris, A., Limousin, O., Etesi, L., Maloney, S. A., Schwartz, R. A., Kuhar, M., Schuller, F., Senthamizh Pavai, V., Musset, S., Ryan, D. F., Kleint, L., Piana, M., Massone, A. M., Benvenuto, F., Sylwester, J., Litwicka, M., Stȩślicki, M., Mrozek, T., Vilmer, N., Fárník, F., Kašparová, J., Mann, G., Gallagher, P. T., Dennis, B. R., Csillaghy, A., Benz, A. O., & Krucker, S. (2021), Astronomy and Astrophysics, 656, A4. [https://ui.adsabs.harvard.edu/abs/2021A&A...656A...4B "STIX X-ray microflare observations during the Solar Orbiter commissioning phase"]

: Shaik, S. B., & Gary, D. E. (2021), The Astrophysical Journal, 919, 44. [https://ui.adsabs.harvard.edu/abs/2021ApJ...919...44S "Implications of Flat Optically Thick Microwave Spectra in Solar Flares for Source Size and Morphology"]

: Kocharov, L., Omodei, N., Mishev, A., Pesce-Rollins, M., Longo, F., Yu, S., Gary, D. E., Vainio, R., & Usoskin, I. (2021), The Astrophysical Journal, 915, 12. [https://ui.adsabs.harvard.edu/abs/2021ApJ...915...12K "Multiple Sources of Solar High-energy Protons"]

: Chen, B., Battaglia, M., Krucker, S., Reeves, K. K., & Glesener, L. (2021), The Astrophysical Journal, 908, L55. [https://ui.adsabs.harvard.edu/abs/2021ApJ...908L..55C "Energetic Electron Distribution of the Coronal Acceleration Region: First Results from Joint Microwave and Hard X-Ray Imaging Spectroscopy"]

: Chhabra, S., Gary, D. E., Hallinan, G., Anderson, M. M., Chen, B., Greenhill, L. J., & Price, D. C. (2021), The Astrophysical Journal, 906, 132. [https://ui.adsabs.harvard.edu/abs/2021ApJ...906..132C "Imaging Spectroscopy of CME-associated Solar Radio Bursts using OVRO-LWA"]
;2020 and earlier

: Reeves, K. K., Polito, V., Chen, B., Galan, G., Yu, S., Liu, W., & Li, G. (2020), The Astrophysical Journal, 905, 165. [https://ui.adsabs.harvard.edu/abs/2020ApJ...905..165R "Hot Plasma Flows and Oscillations in the Loop-top Region During the 2017 September 10 X8.2 Solar Flare"]

: Nindos, A. (2020), Frontiers in Astronomy and Space Sciences, 7, 57. [https://ui.adsabs.harvard.edu/abs/2020FrASS...7...57N "Incoherent Solar Radio Emission"]

: Yu, S., Chen, B., Reeves, K. K., Gary, D. E., Musset, S., Fleishman, G. D., Nita, G. M., & Glesener, L. (2020), The Astrophysical Journal, 900, 17. [https://ui.adsabs.harvard.edu/abs/2020ApJ...900...17Y "Magnetic Reconnection during the Post-impulsive Phase of a Long-duration Solar Flare: Bidirectional Outflows as a Cause of Microwave and X-Ray Bursts"]

: Chen, B., Yu, S., Reeves, K. K., & Gary, D. E. (2020), The Astrophysical Journal, 895, L50. [https://ui.adsabs.harvard.edu/abs/2020ApJ...895L..50C "Microwave Spectral Imaging of an Erupting Magnetic Flux Rope: Implications for the Standard Solar Flare Model in Three Dimensions"]

: Kuroda, N., Fleishman, G. D., Gary, D. E., Nita, G. M., Chen, B., & Yu, S. (2020), Frontiers in Astronomy and Space Sciences, 7, 22. [https://ui.adsabs.harvard.edu/abs/2020FrASS...7...22K "Evolution of Flare-accelerated Electrons Quantified by Spatially Resolved Analysis"]

: Glesener, L., Krucker, S., Duncan, J., Hannah, I. G., Grefenstette, B. W., Chen, B., Smith, D. M., White, S. M., & Hudson, H. (2020), The Astrophysical Journal, 891, L34. [https://ui.adsabs.harvard.edu/abs/2020ApJ...891L..34G "Accelerated Electrons Observed Down to <7 keV in a NuSTAR Solar Microflare"]

: Karlický, M., Chen, B., Gary, D. E., Kašparová, J., & Rybák, J. (2020), The Astrophysical Journal, 889, 72. [https://ui.adsabs.harvard.edu/abs/2020ApJ...889...72K "Drifting Pulsation Structure at the Very Beginning of the 2017 September 10 Limb Flare"]

: Fleishman, G. D., Gary, D. E., Chen, B., Kuroda, N., Yu, S., & Nita, G. M. (2020), Science, 367, 278. [https://ui.adsabs.harvard.edu/abs/2020Sci...367..278F "Decay of the coronal magnetic field can release sufficient energy to power a solar flare"]

: Chen, B., Shen, C., Gary, D. E., Reeves, K. K., Fleishman, G. D., Yu, S., Guo, F., Krucker, S., Lin, J., Nita, G. M., & Kong, X. (2020), Nature Astronomy, 4, 1140. [https://ui.adsabs.harvard.edu/abs/2020NatAs...4.1140C "Measurement of magnetic field and relativistic electrons along a solar flare current sheet"]

: Lee, J. (2018), Journal of Astronomy and Space Sciences, 35, 211. [https://ui.adsabs.harvard.edu/abs/2018JASS...35..211L "Analysis of Solar Microwave Burst Spectrum, I. Nonuniform Magnetic Field"]

: Gary, D. E., Bastian, T. S., Chen, B., Fleishman, G. D., & Glesener, L. (2018), Science with a Next Generation Very Large Array, 517, 99. [https://ui.adsabs.harvard.edu/abs/2018ASPC..517...99G "Radio Observations of Solar Flares"]

: Polito, V., Dudík, J., Kašparová, J., Dzifčáková, E., Reeves, K. K., Testa, P., & Chen, B. (2018), The Astrophysical Journal, 864, 63. [https://ui.adsabs.harvard.edu/abs/2018ApJ...864...63P "Broad Non-Gaussian Fe XXIV Line Profiles in the Impulsive Phase of the 2017 September 10 X8.3-class Flare Observed by Hinode/EIS"]

: Gary, D. E., Chen, B., Dennis, B. R., Fleishman, G. D., Hurford, G. J., Krucker, S., McTiernan, J. M., Nita, G. M., Shih, A. Y., White, S. M., & Yu, S. (2018), The Astrophysical Journal, 863, 83. [https://ui.adsabs.harvard.edu/abs/2018ApJ...863...83G "Microwave and Hard X-Ray Observations of the 2017 September 10 Solar Limb Flare"]

: Fleishman, G. D., Nita, G. M., Kuroda, N., Jia, S., Tong, K., Wen, R. R., & Zhizhuo, Z. (2018), The Astrophysical Journal, 859, 17. [https://ui.adsabs.harvard.edu/abs/2018ApJ...859...17F "Revealing the Evolution of Non-thermal Electrons in Solar Flares Using 3D Modeling"]

: Kuroda, N., Gary, D. E., Wang, H., Fleishman, G. D., Nita, G. M., & Jing, J. (2018), The Astrophysical Journal, 852, 32. [https://ui.adsabs.harvard.edu/abs/2018ApJ...852...32K "Three-dimensional Forward-fit Modeling of the Hard X-Ray and Microwave Emissions of the 2015 June 22 M6.5 Flare"]

: Wang, H., Liu, C., Ahn, K., Xu, Y., Jing, J., Deng, N., Huang, N., Liu, R., Kusano, K., Fleishman, G. D., Gary, D. E., & Cao, W. (2017), Nature Astronomy, 1, 0085. [https://ui.adsabs.harvard.edu/abs/2017NatAs...1E..85W "High-resolution observations of flare precursors in the low solar atmosphere"]

: Nita, G. M., Hickish, J., MacMahon, D., & Gary, D. E. (2016), Journal of Astronomical Instrumentation, 5, 1641009-7366. [https://ui.adsabs.harvard.edu/abs/2016JAI.....541009N "EOVSA Implementation of a Spectral Kurtosis Correlator for Transient Detection and Classification"]

: Nita, G. M., & Gary, D. E. (2016), Journal of Geophysical Research (Space Physics), 121, 7353. [https://ui.adsabs.harvard.edu/abs/2016JGRA..121.7353N "Measurement of duration and signal-to-noise ratio of astronomical transients using a Spectral Kurtosis spectrometer"]

: Wang, Z., Gary, D. E., Fleishman, G. D., & White, S. M. (2015), The Astrophysical Journal, 805, 93. [https://ui.adsabs.harvard.edu/abs/2015ApJ...805...93W "Coronal Magnetography of a Simulated Solar Active Region from Microwave Imaging Spectropolarimetry"]

: Gary, D. E., Fleishman, G. D., & Nita, G. M. (2013), Solar Physics, 288, 549. [https://ui.adsabs.harvard.edu/abs/2013SoPh..288..549G "Magnetography of Solar Flaring Loops with Microwave Imaging Spectropolarimetry"]

== VLA Flare List and Publications ==
See [http://www.ovsa.njit.edu/wiki/index.php/VLA_Data_Survey#List_of_Jansky_VLA_Solar_Observations this link] for a list of flare observations made by the [https://science.nrao.edu/facilities/vla/ Karl G. Jansky Very Large Array] (VLA). Below is a partial list of publications that utilize VLA solar data (see also [https://ui.adsabs.harvard.edu/public-libraries/ZwbjpLo9RS-viufWEoQ95Q this NASA/ADS Library]).
* [https://ui.adsabs.harvard.edu/abs/2022ApJ...940..137L/abstract Luo et al. (2022), ApJ, 940, 137] ''Multiple Regions of Nonthermal Quasiperiodic Pulsations during the Impulsive Phase of a Solar Flare''
* [https://ui.adsabs.harvard.edu/abs/2021ApJ...922..134B/abstract Battaglia et al. (2021), ApJ, 922, 134] ''Multiple Electron Acceleration Instances during a Series of Solar Microflares Observed Simultaneously at X-Rays and Microwaves''
* [https://ui.adsabs.harvard.edu/abs/2021ApJ...911....4L/abstract Luo et al. (2021), ApJ, 911, 4] ''Radio Spectral Imaging of an M8.4 Eruptive Solar Flare: Possible Evidence of a Termination Shock''
* [https://ui.adsabs.harvard.edu/abs/2021ApJ...910...40Z/abstract Zhang et al. (2021), ApJ, 910, 40] ''Multiwavelength Observations of the Formation and Eruption of a Complex Filament''
* [https://ui.adsabs.harvard.edu/abs/2020ApJ...904...94S/abstract Sharma et al. (2020), ApJ, 904, 94] ''Radio and X-Ray Observations of Short-lived Episodes of Electron Acceleration in a Solar Microflare''
* [https://ui.adsabs.harvard.edu/abs/2019ApJ...884...63C/abstract Chen et al. (2019), ApJ, 884, 63] ''Radio Spectroscopic Imaging of a Solar Flare Termination Shock: Split-band Feature as Evidence for Shock Compression''
* [https://ui.adsabs.harvard.edu/abs/2019ApJ...872...71Y/abstract Yu & Chen (2019), ApJ, 872, 71] ''Possible Detection of Subsecond-period Propagating Magnetohydrodynamics Waves in Post-reconnection Magnetic Loops during a Two-ribbon Solar Flare''
* [https://ui.adsabs.harvard.edu/abs/2018ApJ...866...62C/abstract Chen et al. (2018), ApJ, 866, 62] ''Magnetic Reconnection Null Points as the Origin of Semirelativistic Electron Beams in a Solar Jet
''
* [https://ui.adsabs.harvard.edu/abs/2017ApJ...848...77W/abstract Wang et al. (2016), ApJ, 848, 77] ''Dynamic Spectral Imaging of Decimetric Fiber Bursts in an Eruptive Solar Flare''
* [https://ui.adsabs.harvard.edu/abs/2015Sci...350.1238C/abstract Chen et al. (2015), Science, 350, 1238] ''Particle acceleration by a solar flare termination shock''
* [https://ui.adsabs.harvard.edu/abs/2014ApJ...794..149C/abstract Chen et al. (2014), ApJ, 794, 149] ''Direct Evidence of an Eruptive, Filament-hosting Magnetic Flux Rope Leading to a Fast Solar Coronal Mass Ejection''
* [https://ui.adsabs.harvard.edu/abs/2013ApJ...763L..21C/abstract Chen et al. (2013), ApJL, 763, 21] ''Tracing Electron Beams in the Sun's Corona with Radio Dynamic Imaging Spectroscopy''

==Radio Data from Around The Heliosphere==
* [http://ovsa.njit.edu//wiki/index.php/Radio_Data_from_Around_the_World#Radio_Data_Access '' Radio Data '']

=OVRO-LWA Solar-Dedicated Spectroscopic Imager=
The OVRO-LWA (Owens Valley Radio Observatory Long Wavelength Array) has recently been upgraded to include a solar-dedicated beam and two solar imaging modes (slow visibilities of 352 antennas with a 10-s cadence, and fast visibilities of 48 antennas with a 0.1-s cadence). The large collecting area and excellent calibration provide unprecedented high-sensitivity imaging of the quiet Sun and bursts. The array is currently in commissioning and observations are not yet continuous, but they are becoming more so. See the daily realtime data at http://ovsa.njit.edu/status.php for '''real-time display of the spectrogram and a selection of images''', both updated on a 1-min cadence.

==Solar-Dedicated Modes==
===Beamformer===
The beamformer uses the 256 core antennas to form a synthesized beam of more than 1 degree in size that tracks the Sun from sunrise to sunset. This permits a continuous record of the full-Stokes total flux (without spatial resolution) of the Sun (a dynamic spectrum) with 24 kHz frequency resolution (3072 frequencies from 15-90 MHz) and as low as 1 ms time resolution.

===Slow Visibility Imaging===
In this mode, the entire 352-element array is interferometrically correlated to provide visibilities for imaging at all 3072 frequencies at 10-s time resolution. This is ideal for imaging quiet Sun and slowly-varying emission such as coronal mass ejections and active region variability.

===Fast Visibility Imaging===
In this mode, a subset of 48 antennas (chosen to include mainly outer antennas to maintain good spatial resolution) is interferometrically correlated to provide visibilities for imaging at 768 frequencies (96 kHz frequency resolution) at 0.1-s time resolution. This is ideal for imaging rapidly varying emission such as type II and type III bursts as well as many other solar spectral fine structures.

==Inital Data Access==
In its current commissioning state, we try to run the beamformer and imaging pipeline every day in real-time since November 2023 (no latency for beamforming spectrograms and 5-10 min latency for images). Quicklook real-time spectrograms/images can be accessed from http://ovsa.njit.edu/status.php. To access data from previous days, use the following links (replace yyyymmdd with the date you desire):
* Quicklook beamformer total-power spectrograms: http://ovsa.njit.edu/lwa-data/1min_spectra/yyyymmdd/. Check this link for additional daily plots [[Daily OVRO-LWA Beamformer Data]].
* Quicklook multi-frequency movies at 1-min cadence: http://ovsa.njit.edu/lwa-data/1min_images/yyyymmdd/movie_yyyy-mm-dd.html

Note our pipeline processing development is still in the early phase. For example, absolute flux calibrations have not been done for the beamformer spectrograms. Also, artificial effects (including ionospheric refraction effects) are present in the images that cause distortions/shifts. We caution interested users only to consider them for quick-look purposes at this point. Please contact the EOVSA PIs (Dale Gary, Bin Chen) if you intend to use them for science.

== OVRO-LWA Observing Log ==
[https://docs.google.com/document/d/1QDWw5y4HpcE7CSpzXwftMqQT4FDgNJj-6fRrgWrqdug/edit?usp=sharing Link to the OVRO-LWA solar observing logs (in Google Doc)]

EOVSA Data Products

2024-03-29T15:42:43Z

Binchen: /* Level 0.5 - Calibrated visibility data */

=Introduction=
EOVSA observes the full disk of the Sun at all times when the Sun is >10 degrees above the local horizon (season dependent and ranges from 7-12 hours duration centered on 20 UT). EOVSA records data at 451 science frequency channels each second, in four polarization products, as well as additional total flux measurements from each individual antenna. Figure 1 summarizes the different levels of data we produce. The later sections will give a more detailed description and usage examples.
[[File:pipeline_flowchart.jpg|center|600px|EOVSA pipeline block diagram/flow chart ]]

=Level 0 - Raw visibility data from the instrument=

As outlined in Figure 1, EOVSA creates raw data products in the left-hand column (labeled Level 0). This includes observations of cosmic sources for phase calibration, and gain and pointing observations required for total power calibration.

==Raw "Interim" Database (IDB) visibility data==
Full-resolution raw "Interim" Database (IDB) visibility data. They are stored in Miriad format, and hence may not be that useful for most people. Be patient after clicking the link--this is a very long list of directories, one for each available date. These data can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/IDB/

==Raw 1-min-averaged visibility data==
This is the same as for the IDB data, except with 1-minute time integration applied. This is typically not useful for flares, but is perfectly fine for imaging active regions and full Sun. These data can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/UDB/

=Level 0.5 - Calibrated visibility data=
After applying calibration and other preliminary processing to the raw (level 0) data, we create the CASA ms’s in the second column in Figure 1 (labeled "level 0.5"). These visibility data are in the Fourier domain of the true images in the plane of the sky and are not immediately ready for spectral imaging analysis yet. However, they have all of the required content to produce images and spectrogram data in standard FITS format (level 1.0). We provide a set of standard ms’s for each day (red boxes in Figure 1), for use by researchers who know how to deal with visibility data. These data are more suitable for experienced users to exploit the full potential of EOVSA data, such as spatially resolved spectral analysis. Processing these data requires CASA or sunCASA (https://github.com/suncasa/suncasa-src). Please refer to our tutorial at [[EOVSA_Data_Analysis_Tutorial]].

==Calibrated full-resolution visibility data for flare events==
Calibrated and self-calibrated visibility data for flare events (purple boxes in Figure 1) will typically be available within 7 days after they are taken. They will be released at our flare list site soon: https://ovsa.njit.edu/flarelist

==Self-calibrated 1-min-averaged visibility data==
EOVSA 1-min averaged visibility data in CASA ms format can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/UDBms_slfcaled

=Level 1.0 - Images and spectrogram data in standard FITS format =

Level 1.0 data are for users who prefer to work with spectrogram (frequency-time) and image data directly, which are also outputs of the pipeline system shown in Figure 1 (orange boxes). They are perfectly suitable to be used as context data for comparison with other multi-wavelength observations but are not (yet) intended for quantitative spatially resolved spectral analysis.

Spectrograms are provided as standard FITS tables containing the frequency list, list of times, and data in both total power (TP) and a sum of amplitudes over intermediate-length baselines (cross power or XP). Likewise, image data products are in FITS format with standard keywords and are converted into the Helioprojective Cartesian coordinate system compatible with the World Coordinate System (WCS) convention, along with correct registration for the spatial, spectral, and temporal coordinates. Both the spectrogram and image data products are calibrated and have physical radio intensity units (sfu for spectrograms and brightness temperature for radio images).

We provide the following level 1 data products:
* Synoptic products:
** '''All-day spectrograms''':
** '''All-day synoptic images''': Full disk images at 6 selected frequency bands centered at 1.4, 3.0, 4.5, 6.8, 10.2, and 13.9 GHz are produced once per day utilizing the earth-rotation synthesis, calibrated in brightness temperature. This is because EOVSA has a limited number of baselines and we need a long integration to fill up the uv domain in order to make full-disk images.
* Event-based products:
** '''Flare spectrograms''': These are full time and frequency resolution spectrograms produced from the median of calibrated cross-power visibilities in FITS format, cropped to cover the flare duration. Preflare background is also subtracted. Compared to total-power spectrograms, these spectrograms have the advantage of revealing details of the flare evolution by "filtering out" the large-scale, continuous background from the visibilities. Note that for certain flares that have a large source size, the flux can be lower than its true values (as a fraction of the flux will be "resolved out").
** '''Pipeline-produced spectral images''': We also have a semi-automated flare imaging pipeline to produce calibrated (and self-calibrated) images at 12-s cadence at up to 10 frequency bands. They are saved in standard FITS format and have been registered into Helioprojective coordinates. They can be read by SSWIDL or astropy/sunpy. These data have already been calibrated to physical units and are usually good to be compared with context data. But please be cautious when using them for quantitative spectral analysis.

{| class="wikitable"
|+ Summary of EOVSA Level 1 Data Products
|-
! scope="col"| Category
! scope="col"| Data Product
! scope="col"| Naming Convention
! scope="col"| Download Link
|-
! rowspan="2" | Synoptic Spectrograms
| All-day TP Spectrograms
| EOVSA_TPall_yyyymmdd.fts
!rowspan="9" | https://ovsa.njit.edu/browser
|-
| All-day XP Spectrograms
| EOVSA_XPall_yyyymmdd.fts
|-
! rowspan="7" | Synoptic Images
|-
| Synoptic 1.4 GHz images
| eovsa_yyyymmdd.spw00-01.tb.disk.fits
|-
| Synoptic 3.0 GHz images
| eovsa_yyyymmdd.spw02-05.tb.disk.fits
|-
| Synoptic 4.5 GHz images
| eovsa_yyyymmdd.spw06-10.tb.disk.fits
|-
| Synoptic 6.8 GHz images
| eovsa_yyyymmdd.spw11-20.tb.disk.fits
|-
| Synoptic 10.2 GHz images
| eovsa_yyyymmdd.spw21-30.tb.disk.fits
|-
| Synoptic 13.9 GHz images
| eovsa_yyyymmdd.spw31-43.tb.disk.fits
|-
! rowspan="1" | Flare Spectrograms
| Full-resolution cross-power Spectrogram
| eovsa.spec.flare_id_YYYYMMDDHHMMSS.fits
!rowspan="2" | https://ovsa.njit.edu/flarelist
|-
! rowspan="1" | Flare Spectral Images
| Pipeline-produced spectral images
| eovsa.lev1_mbd_12s.YYYY-MM-DDTHHMMSSZ.image.fits
|-
|}

==Browsing and Downloading level 1 data==
[[File:eovsa_browser.jpg|right|thumb|EOVSA Browser]]
[[file:EOVSA_flarelist.jpg|right|thumb|EOVSA Flare List]]
===Synoptic level 1 data===
EOVSA Level 1 synoptic data products can be retrieved with the following steps:
* Go to [http://ovsa.njit.edu/browser/ EOVSA browser] page.
* Browse to the date of interest.
* Click "synoptic fits" button next to the calendar tool.
* Select the data product based on the names listed in the table above.

===Flare level 1 data===
EOVSA flare list with spectrograms and spectral images can be queried and downloaded at https://ovsa.njit.edu/flarelist. Users can use the top box to select a time range of interest and query our flare list. The results are displayed in the dropdown box. An interactive plot of the flare light curves will be shown at the bottom of the page once an event is highlighted (by clicking on the flare ID). Quicklook plots and FITS files of the spectrograms and flare movies can be accessed by clicking the icons in each flare record.

==Reading and Using level 1 data==
===Introduction===
All our level 1 data products are in FITS format. All the images have standard, WCS-compatible coordinates. Users can use their favorite method to read these files. In the following, we provide minimal examples to read them with Astropy and Sunpy.

===Event-Based Data Products===
* An example of how to read and plot the flare spectrograms and images in Python (with Astropy and SunPy) can be accessed at [https://colab.research.google.com/drive/1Y3ONWCxLPYvWda5_LqFNxafJtwZDNJBD?usp=sharing#scrollTo=ueiMoHbdxfo- this Google Colab Jupyter notebook].
* We are working on an example with SSWIDL and will release it soon.

===Synoptic Data Products===

===All-day Spectrograms===
To read a spectrogram file in Python using the suncasa library:

<pre style="background-color: #FCEBD9;">
from suncasa.eovsa import eovsa_dspec as ds
from astropy.time import Time
from matplotlib.colors import LogNorm
## Read EOVSA Dynamic Spectrum FITS file <filename>
filename = 'EOVSA_TPall_20170713.fts'
s = ds.get_dspec(filename, doplot=True, cmap='gist_heat', norm=LogNorm(vmax=2.1e3, vmin=40))
## To access the data in the spectrogram object, use
spec = s['spectrogram'] ## (Array of amplitudes in SFU, of size nfreq,ntimes)
fghz = s['spectrum_axis'] ## (Array of frequencies in GHz, of size nfreq)
tim = Time(s['time_axis'], format='mjd') ## (Array of UT times in astropy.time object, of size ntimes)

</pre>

The '''get_dspec''' function is accessible on [https://github.com/suncasa/suncasa-src/blob/master/suncasa/eovsa/eovsa_dspec.py GitHub]. For comprehensive guidance, please refer to suncasa's [https://suncasa-src.readthedocs.io/en/latest/autoapi/suncasa/eovsa/eovsa_dspec/index.html ReadtheDocs page].
[[File:TPSP.jpeg|center|500px]]

The following code will read the spectrogram file in IDL:

<pre style="background-color: #FCEBD9;">
function dspec,filename,doplot=doplot
; Read EOVSA Dynamic Spectrum FITS file <filename> and return a spectrogram object.
; Optionally show an overview plot if doplot switch is set
;
; Usage:
; s = dspec(<filename>) ; Returns spectrogram object
; s = dspec(<filename>,/doplot) ; Plots spectrum and returns spectrogram object
;
; To access the data in the spectrogram object, use
; spec = s.get(/spectrogram) (Array of amplitudes in SFU, of size ntimes, nfreq)
; fghz = s.get(/spectrum_axis) (Array of frequencies in GHz, of size nfreq)
; ut = s.get(/time_axis) (Array of UT times in anytim format, of size ntimes)

default,doplot,0
spec = mrdfits(filename,0)
freq = mrdfits(filename,1)
time = mrdfits(filename,2)
fghz = freq.sfreq
ut = anytim(time)
s = spectrogram(spec,ut,fghz)
if doplot then begin
window,/free,xsiz=1024,ysiz=600
; Find min and max of data from 5% to 95% of sorted array (eliminates outliers)
sarr = sort(spec)
dlim = minmax(spec[sarr[n_elements(sarr)*0.05:n_elements(sarr)*0.95]])
; Set drange with margin factor of 2 on low end and 5 on high end
s.set,drange=dlim*[0.5,5]
loadct,3
s.plot,/log,/xsty,/ysty,ytitle='Frequency [GHz]',charsize=1.5
endif
return,s
end
</pre>
[[File:IDL_TPSP.png|center|500px]]

===Synoptic 6-band Images===
Full disk images at 6 selected frequency bands centered at 1.4, 3.0, 4.5, 6.8, 10.2, and 13.9 GHz are provided once per day, calibrated in brightness temperature. [[File:synoptic_image.jpg| center |400px]]

The EOVSA full disk image FITS files are compressed with the RICE algorithm implemented in the FITS file handling module (astropy.io.fits) in Astropy. EOVSA FITS files are very similar to the compressed SDO/AIA FITS files from JSOC. Popular coding languages can easily read compressed images directly.

In IDL, you can use read_sdo in the ONTOLOGY package, which should be installed by default in SolarSoftWare (SSW), to read compressed EOVSA FITS files. The following code will read the EOVSA image FITS file in SSWIDL:

<pre style="background-color: #FCEBD9;">
read_sdo,'eovsa_20191225.spw11-20.tb.disk.fits',header,data,/UNCOMP_DELETE
index2map,header,data,eomap
plot_map,eomap
</pre>

[[File:eovsa_20191225_image_sswidl.jpg| center |250px]]

In Python, you can use SunPy map module to read EOVAS FITS files. SunPy is an open solar data analysis environment for Python. The installation instruction can be found at [https://sunpy.org/ SunPy official website].
<pre style="background-color: #FCEBD9;">
import matplotlib.pyplot as plt
from sunpy import map as smap
eofile='eovsa_20191225.spw11-20.tb.disk.fits'
eomap = smap.Map(eofile)
eomap.plot()
plt.show()
</pre>
[[File:eovsa_20191225_image_py.jpg| center |250px]]

We have developed a package for EOVSA data processing and analysis:
[https://github.com/suncasa/suncasa SunCASA] A wrapper around [https://casa.nrao.edu/ CASA (the Common Astronomy Software Applications package)] for synthesis imaging and visualizing solar spectral imaging data. CASA is one of the leading software tools for "supporting the data post-processing needs of the next generation of radio astronomical telescopes such as ALMA and VLA", an international effort led by the [https://public.nrao.edu/ National Radio Astronomy Observatory]. The current version of CASA uses Python (2.7) interface. More information about CASA can be found on [https://casa.nrao.edu/ NRAO's CASA website ]. Note, CASA is available ONLY on UNIX-BASED PLATFORMS (and therefore, so is SunCASA). We are developing a new version of SunCASA based on CASA 6 (which offers a modular approach) so that users have the flexibility to build CASA tools and tasks in their Python environment.

Please [http://www.ovsa.njit.edu/wiki/index.php/SunCASA_Installation follow this link] for details regarding the installation of SunCASA on your own machine (only available on Unix-bases OS). This will take you to another page.

EOVSA Data Products

2024-03-29T15:13:49Z

Binchen: /* Level 1.0 - Images and spectrogram data in standard FITS format */

=Introduction=
EOVSA observes the full disk of the Sun at all times when the Sun is >10 degrees above the local horizon (season dependent and ranges from 7-12 hours duration centered on 20 UT). EOVSA records data at 451 science frequency channels each second, in four polarization products, as well as additional total flux measurements from each individual antenna. Figure 1 summarizes the different levels of data we produce. The later sections will give a more detailed description and usage examples.
[[File:pipeline_flowchart.jpg|center|600px|EOVSA pipeline block diagram/flow chart ]]

=Level 0 - Raw visibility data from the instrument=

As outlined in Figure 1, EOVSA creates raw data products in the left-hand column (labeled Level 0). This includes observations of cosmic sources for phase calibration, and gain and pointing observations required for total power calibration.

==Raw "Interim" Database (IDB) visibility data==
Full-resolution raw "Interim" Database (IDB) visibility data. They are stored in Miriad format, and hence may not be that useful for most people. Be patient after clicking the link--this is a very long list of directories, one for each available date. These data can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/IDB/

==Raw 1-min-averaged visibility data==
This is the same as for the IDB data, except with 1-minute time integration applied. This is typically not useful for flares, but is perfectly fine for imaging active regions and full Sun. These data can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/UDB/

=Level 0.5 - Calibrated visibility data=
After applying calibration and other preliminary processing to the raw (level 0) data, we create the CASA ms’s in the second column in Figure 1 (labeled "level 0.5"). These visibility data are in the Fourier domain of the true images in the plane of the sky and are not immediately ready for spectral imaging analysis yet. However, they have all of the required content to produce images and spectrogram data in standard FITS format (level 1.0). We provide a set of standard ms’s for each day (red boxes in Figure 1), for use by researchers who know how to deal with visibility data. These data are more suitable for experienced users to exploit the full potential of EOVSA data, such as spatially resolved spectral analysis. Processing these data requires CASA or sunCASA (https://github.com/suncasa/suncasa-src). Please refer to our tutorial at [[EOVSA_Data_Analysis_Tutorial_2022]].

==Calibrated full-resolution visibility data for flare events==
Calibrated and self-calibrated visibility data for flare events (purple boxes in Figure 1) will typically be available within 7 days after they are taken. They will be released at our flare list site soon: https://ovsa.njit.edu/flarelist

==Self-calibrated 1-min-averaged visibility data==
EOVSA 1-min averaged visibility data in CASA ms format can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/UDBms_slfcaled

=Level 1.0 - Images and spectrogram data in standard FITS format =

Level 1.0 data are for users who prefer to work with spectrogram (frequency-time) and image data directly, which are also outputs of the pipeline system shown in Figure 1 (orange boxes). They are perfectly suitable to be used as context data for comparison with other multi-wavelength observations but are not (yet) intended for quantitative spatially resolved spectral analysis.

Spectrograms are provided as standard FITS tables containing the frequency list, list of times, and data in both total power (TP) and a sum of amplitudes over intermediate-length baselines (cross power or XP). Likewise, image data products are in FITS format with standard keywords and are converted into the Helioprojective Cartesian coordinate system compatible with the World Coordinate System (WCS) convention, along with correct registration for the spatial, spectral, and temporal coordinates. Both the spectrogram and image data products are calibrated and have physical radio intensity units (sfu for spectrograms and brightness temperature for radio images).

We provide the following level 1 data products:
* Synoptic products:
** '''All-day spectrograms''':
** '''All-day synoptic images''': Full disk images at 6 selected frequency bands centered at 1.4, 3.0, 4.5, 6.8, 10.2, and 13.9 GHz are produced once per day utilizing the earth-rotation synthesis, calibrated in brightness temperature. This is because EOVSA has a limited number of baselines and we need a long integration to fill up the uv domain in order to make full-disk images.
* Event-based products:
** '''Flare spectrograms''': These are full time and frequency resolution spectrograms produced from the median of calibrated cross-power visibilities in FITS format, cropped to cover the flare duration. Preflare background is also subtracted. Compared to total-power spectrograms, these spectrograms have the advantage of revealing details of the flare evolution by "filtering out" the large-scale, continuous background from the visibilities. Note that for certain flares that have a large source size, the flux can be lower than its true values (as a fraction of the flux will be "resolved out").
** '''Pipeline-produced spectral images''': We also have a semi-automated flare imaging pipeline to produce calibrated (and self-calibrated) images at 12-s cadence at up to 10 frequency bands. They are saved in standard FITS format and have been registered into Helioprojective coordinates. They can be read by SSWIDL or astropy/sunpy. These data have already been calibrated to physical units and are usually good to be compared with context data. But please be cautious when using them for quantitative spectral analysis.

{| class="wikitable"
|+ Summary of EOVSA Level 1 Data Products
|-
! scope="col"| Category
! scope="col"| Data Product
! scope="col"| Naming Convention
! scope="col"| Download Link
|-
! rowspan="2" | Synoptic Spectrograms
| All-day TP Spectrograms
| EOVSA_TPall_yyyymmdd.fts
!rowspan="9" | https://ovsa.njit.edu/browser
|-
| All-day XP Spectrograms
| EOVSA_XPall_yyyymmdd.fts
|-
! rowspan="7" | Synoptic Images
|-
| Synoptic 1.4 GHz images
| eovsa_yyyymmdd.spw00-01.tb.disk.fits
|-
| Synoptic 3.0 GHz images
| eovsa_yyyymmdd.spw02-05.tb.disk.fits
|-
| Synoptic 4.5 GHz images
| eovsa_yyyymmdd.spw06-10.tb.disk.fits
|-
| Synoptic 6.8 GHz images
| eovsa_yyyymmdd.spw11-20.tb.disk.fits
|-
| Synoptic 10.2 GHz images
| eovsa_yyyymmdd.spw21-30.tb.disk.fits
|-
| Synoptic 13.9 GHz images
| eovsa_yyyymmdd.spw31-43.tb.disk.fits
|-
! rowspan="1" | Flare Spectrograms
| Full-resolution cross-power Spectrogram
| eovsa.spec.flare_id_YYYYMMDDHHMMSS.fits
!rowspan="2" | https://ovsa.njit.edu/flarelist
|-
! rowspan="1" | Flare Spectral Images
| Pipeline-produced spectral images
| eovsa.lev1_mbd_12s.YYYY-MM-DDTHHMMSSZ.image.fits
|-
|}

==Browsing and Downloading level 1 data==
[[File:eovsa_browser.jpg|right|thumb|EOVSA Browser]]
[[file:EOVSA_flarelist.jpg|right|thumb|EOVSA Flare List]]
===Synoptic level 1 data===
EOVSA Level 1 synoptic data products can be retrieved with the following steps:
* Go to [http://ovsa.njit.edu/browser/ EOVSA browser] page.
* Browse to the date of interest.
* Click "synoptic fits" button next to the calendar tool.
* Select the data product based on the names listed in the table above.

===Flare level 1 data===
EOVSA flare list with spectrograms and spectral images can be queried and downloaded at https://ovsa.njit.edu/flarelist. Users can use the top box to select a time range of interest and query our flare list. The results are displayed in the dropdown box. An interactive plot of the flare light curves will be shown at the bottom of the page once an event is highlighted (by clicking on the flare ID). Quicklook plots and FITS files of the spectrograms and flare movies can be accessed by clicking the icons in each flare record.

==Reading and Using level 1 data==
===Introduction===
All our level 1 data products are in FITS format. All the images have standard, WCS-compatible coordinates. Users can use their favorite method to read these files. In the following, we provide minimal examples to read them with Astropy and Sunpy.

===Event-Based Data Products===
* An example of how to read and plot the flare spectrograms and images in Python (with Astropy and SunPy) can be accessed at [https://colab.research.google.com/drive/1Y3ONWCxLPYvWda5_LqFNxafJtwZDNJBD?usp=sharing#scrollTo=ueiMoHbdxfo- this Google Colab Jupyter notebook].
* We are working on an example with SSWIDL and will release it soon.

===Synoptic Data Products===

===All-day Spectrograms===
To read a spectrogram file in Python using the suncasa library:

<pre style="background-color: #FCEBD9;">
from suncasa.eovsa import eovsa_dspec as ds
from astropy.time import Time
from matplotlib.colors import LogNorm
## Read EOVSA Dynamic Spectrum FITS file <filename>
filename = 'EOVSA_TPall_20170713.fts'
s = ds.get_dspec(filename, doplot=True, cmap='gist_heat', norm=LogNorm(vmax=2.1e3, vmin=40))
## To access the data in the spectrogram object, use
spec = s['spectrogram'] ## (Array of amplitudes in SFU, of size nfreq,ntimes)
fghz = s['spectrum_axis'] ## (Array of frequencies in GHz, of size nfreq)
tim = Time(s['time_axis'], format='mjd') ## (Array of UT times in astropy.time object, of size ntimes)

</pre>

The '''get_dspec''' function is accessible on [https://github.com/suncasa/suncasa-src/blob/master/suncasa/eovsa/eovsa_dspec.py GitHub]. For comprehensive guidance, please refer to suncasa's [https://suncasa-src.readthedocs.io/en/latest/autoapi/suncasa/eovsa/eovsa_dspec/index.html ReadtheDocs page].
[[File:TPSP.jpeg|center|500px]]

The following code will read the spectrogram file in IDL:

<pre style="background-color: #FCEBD9;">
function dspec,filename,doplot=doplot
; Read EOVSA Dynamic Spectrum FITS file <filename> and return a spectrogram object.
; Optionally show an overview plot if doplot switch is set
;
; Usage:
; s = dspec(<filename>) ; Returns spectrogram object
; s = dspec(<filename>,/doplot) ; Plots spectrum and returns spectrogram object
;
; To access the data in the spectrogram object, use
; spec = s.get(/spectrogram) (Array of amplitudes in SFU, of size ntimes, nfreq)
; fghz = s.get(/spectrum_axis) (Array of frequencies in GHz, of size nfreq)
; ut = s.get(/time_axis) (Array of UT times in anytim format, of size ntimes)

default,doplot,0
spec = mrdfits(filename,0)
freq = mrdfits(filename,1)
time = mrdfits(filename,2)
fghz = freq.sfreq
ut = anytim(time)
s = spectrogram(spec,ut,fghz)
if doplot then begin
window,/free,xsiz=1024,ysiz=600
; Find min and max of data from 5% to 95% of sorted array (eliminates outliers)
sarr = sort(spec)
dlim = minmax(spec[sarr[n_elements(sarr)*0.05:n_elements(sarr)*0.95]])
; Set drange with margin factor of 2 on low end and 5 on high end
s.set,drange=dlim*[0.5,5]
loadct,3
s.plot,/log,/xsty,/ysty,ytitle='Frequency [GHz]',charsize=1.5
endif
return,s
end
</pre>
[[File:IDL_TPSP.png|center|500px]]

===Synoptic 6-band Images===
Full disk images at 6 selected frequency bands centered at 1.4, 3.0, 4.5, 6.8, 10.2, and 13.9 GHz are provided once per day, calibrated in brightness temperature. [[File:synoptic_image.jpg| center |400px]]

The EOVSA full disk image FITS files are compressed with the RICE algorithm implemented in the FITS file handling module (astropy.io.fits) in Astropy. EOVSA FITS files are very similar to the compressed SDO/AIA FITS files from JSOC. Popular coding languages can easily read compressed images directly.

In IDL, you can use read_sdo in the ONTOLOGY package, which should be installed by default in SolarSoftWare (SSW), to read compressed EOVSA FITS files. The following code will read the EOVSA image FITS file in SSWIDL:

<pre style="background-color: #FCEBD9;">
read_sdo,'eovsa_20191225.spw11-20.tb.disk.fits',header,data,/UNCOMP_DELETE
index2map,header,data,eomap
plot_map,eomap
</pre>

[[File:eovsa_20191225_image_sswidl.jpg| center |250px]]

In Python, you can use SunPy map module to read EOVAS FITS files. SunPy is an open solar data analysis environment for Python. The installation instruction can be found at [https://sunpy.org/ SunPy official website].
<pre style="background-color: #FCEBD9;">
import matplotlib.pyplot as plt
from sunpy import map as smap
eofile='eovsa_20191225.spw11-20.tb.disk.fits'
eomap = smap.Map(eofile)
eomap.plot()
plt.show()
</pre>
[[File:eovsa_20191225_image_py.jpg| center |250px]]

We have developed a package for EOVSA data processing and analysis:
[https://github.com/suncasa/suncasa SunCASA] A wrapper around [https://casa.nrao.edu/ CASA (the Common Astronomy Software Applications package)] for synthesis imaging and visualizing solar spectral imaging data. CASA is one of the leading software tools for "supporting the data post-processing needs of the next generation of radio astronomical telescopes such as ALMA and VLA", an international effort led by the [https://public.nrao.edu/ National Radio Astronomy Observatory]. The current version of CASA uses Python (2.7) interface. More information about CASA can be found on [https://casa.nrao.edu/ NRAO's CASA website ]. Note, CASA is available ONLY on UNIX-BASED PLATFORMS (and therefore, so is SunCASA). We are developing a new version of SunCASA based on CASA 6 (which offers a modular approach) so that users have the flexibility to build CASA tools and tasks in their Python environment.

Please [http://www.ovsa.njit.edu/wiki/index.php/SunCASA_Installation follow this link] for details regarding the installation of SunCASA on your own machine (only available on Unix-bases OS). This will take you to another page.

EOVSA Data Products

2024-03-29T15:13:03Z

Binchen: /* Introduction */

=Introduction=
EOVSA observes the full disk of the Sun at all times when the Sun is >10 degrees above the local horizon (season dependent and ranges from 7-12 hours duration centered on 20 UT). EOVSA records data at 451 science frequency channels each second, in four polarization products, as well as additional total flux measurements from each individual antenna. Figure 1 summarizes the different levels of data we produce. The later sections will give a more detailed description and usage examples.
[[File:pipeline_flowchart.jpg|center|600px|EOVSA pipeline block diagram/flow chart ]]

=Level 0 - Raw visibility data from the instrument=

As outlined in Figure 1, EOVSA creates raw data products in the left-hand column (labeled Level 0). This includes observations of cosmic sources for phase calibration, and gain and pointing observations required for total power calibration.

==Raw "Interim" Database (IDB) visibility data==
Full-resolution raw "Interim" Database (IDB) visibility data. They are stored in Miriad format, and hence may not be that useful for most people. Be patient after clicking the link--this is a very long list of directories, one for each available date. These data can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/IDB/

==Raw 1-min-averaged visibility data==
This is the same as for the IDB data, except with 1-minute time integration applied. This is typically not useful for flares, but is perfectly fine for imaging active regions and full Sun. These data can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/UDB/

=Level 0.5 - Calibrated visibility data=
After applying calibration and other preliminary processing to the raw (level 0) data, we create the CASA ms’s in the second column in Figure 1 (labeled "level 0.5"). These visibility data are in the Fourier domain of the true images in the plane of the sky and are not immediately ready for spectral imaging analysis yet. However, they have all of the required content to produce images and spectrogram data in standard FITS format (level 1.0). We provide a set of standard ms’s for each day (red boxes in Figure 1), for use by researchers who know how to deal with visibility data. These data are more suitable for experienced users to exploit the full potential of EOVSA data, such as spatially resolved spectral analysis. Processing these data requires CASA or sunCASA (https://github.com/suncasa/suncasa-src). Please refer to our tutorial at [[EOVSA_Data_Analysis_Tutorial_2022]].

==Calibrated full-resolution visibility data for flare events==
Calibrated and self-calibrated visibility data for flare events (purple boxes in Figure 1) will typically be available within 7 days after they are taken. They will be released at our flare list site soon: https://ovsa.njit.edu/flarelist

==Self-calibrated 1-min-averaged visibility data==
EOVSA 1-min averaged visibility data in CASA ms format can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/UDBms_slfcaled

=Level 1.0 - Images and spectrogram data in standard FITS format =

Level 1.0 data are for users who prefer to work with spectrogram (frequency-time) and image data directly, which are also outputs of the pipeline system shown in Figure 1 (orange boxes). They are perfectly suitable to be used as context data for comparison with other multi-wavelength observations but are not (yet) intended for quantitative spatially resolved spectral analysis.

Spectrograms are provided as standard FITS tables containing the frequency list, list of times, and data in both total power (TP) and a sum of amplitudes over intermediate-length baselines (cross power or XP). Likewise, image data products are in FITS format with standard keywords and are converted into the Helioprojective Cartesian coordinate system compatible with the World Coordinate System (WCS) convention, along with correct registration for the spatial, spectral, and temporal coordinates. Both the spectrogram and image data products are calibrated and have physical radio intensity units (sfu for spectrograms and brightness temperature for radio images).

We provide the following data products:
* Synoptic products:
** '''All-day spectrograms''':
** '''All-day synoptic images''': Full disk images at 6 selected frequency bands centered at 1.4, 3.0, 4.5, 6.8, 10.2, and 13.9 GHz are produced once per day utilizing the earth-rotation synthesis, calibrated in brightness temperature. This is because EOVSA has a limited number of baselines and we need a long integration to fill up the uv domain in order to make full-disk images.
* Event-based products:
** '''Flare spectrograms''': These are full time and frequency resolution spectrograms produced from the median of calibrated cross-power visibilities in FITS format, cropped to cover the flare duration. Preflare background is also subtracted. Compared to total-power spectrograms, these spectrograms have the advantage of revealing details of the flare evolution by "filtering out" the large-scale, continuous background from the visibilities. Note that for certain flares that have a large source size, the flux can be lower than its true values (as a fraction of the flux will be "resolved out").
** '''Pipeline-produced spectral images''': We also have a semi-automated flare imaging pipeline to produce calibrated (and self-calibrated) images at 12-s cadence at up to 10 frequency bands. They are saved in standard FITS format and have been registered into Helioprojective coordinates. They can be read by SSWIDL or astropy/sunpy. These data have already been calibrated to physical units and are usually good to be compared with context data. But please be cautious when using them for quantitative spectral analysis.

{| class="wikitable"
|+ Summary of EOVSA Level 1 Data Products
|-
! scope="col"| Category
! scope="col"| Data Product
! scope="col"| Naming Convention
! scope="col"| Download Link
|-
! rowspan="2" | Synoptic Spectrograms
| All-day TP Spectrograms
| EOVSA_TPall_yyyymmdd.fts
!rowspan="9" | https://ovsa.njit.edu/browser
|-
| All-day XP Spectrograms
| EOVSA_XPall_yyyymmdd.fts
|-
! rowspan="7" | Synoptic Images
|-
| Synoptic 1.4 GHz images
| eovsa_yyyymmdd.spw00-01.tb.disk.fits
|-
| Synoptic 3.0 GHz images
| eovsa_yyyymmdd.spw02-05.tb.disk.fits
|-
| Synoptic 4.5 GHz images
| eovsa_yyyymmdd.spw06-10.tb.disk.fits
|-
| Synoptic 6.8 GHz images
| eovsa_yyyymmdd.spw11-20.tb.disk.fits
|-
| Synoptic 10.2 GHz images
| eovsa_yyyymmdd.spw21-30.tb.disk.fits
|-
| Synoptic 13.9 GHz images
| eovsa_yyyymmdd.spw31-43.tb.disk.fits
|-
! rowspan="1" | Flare Spectrograms
| Full-resolution cross-power Spectrogram
| eovsa.spec.flare_id_YYYYMMDDHHMMSS.fits
!rowspan="2" | https://ovsa.njit.edu/flarelist
|-
! rowspan="1" | Flare Spectral Images
| Pipeline-produced spectral images
| eovsa.lev1_mbd_12s.YYYY-MM-DDTHHMMSSZ.image.fits
|-
|}

==Browsing and Downloading level 1 data==
[[File:eovsa_browser.jpg|right|thumb|EOVSA Browser]]
[[file:EOVSA_flarelist.jpg|right|thumb|EOVSA Flare List]]
===Synoptic level 1 data===
EOVSA Level 1 synoptic data products can be retrieved with the following steps:
* Go to [http://ovsa.njit.edu/browser/ EOVSA browser] page.
* Browse to the date of interest.
* Click "synoptic fits" button next to the calendar tool.
* Select the data product based on the names listed in the table above.

===Flare level 1 data===
EOVSA flare list with spectrograms and spectral images can be queried and downloaded at https://ovsa.njit.edu/flarelist. Users can use the top box to select a time range of interest and query our flare list. The results are displayed in the dropdown box. An interactive plot of the flare light curves will be shown at the bottom of the page once an event is highlighted (by clicking on the flare ID). Quicklook plots and FITS files of the spectrograms and flare movies can be accessed by clicking the icons in each flare record.

==Reading and Using level 1 data==
===Introduction===
All our level 1 data products are in FITS format. All the images have standard, WCS-compatible coordinates. Users can use their favorite method to read these files. In the following, we provide minimal examples to read them with Astropy and Sunpy.

===Event-Based Data Products===
* An example of how to read and plot the flare spectrograms and images in Python (with Astropy and SunPy) can be accessed at [https://colab.research.google.com/drive/1Y3ONWCxLPYvWda5_LqFNxafJtwZDNJBD?usp=sharing#scrollTo=ueiMoHbdxfo- this Google Colab Jupyter notebook].
* We are working on an example with SSWIDL and will release it soon.

===Synoptic Data Products===

===All-day Spectrograms===
To read a spectrogram file in Python using the suncasa library:

<pre style="background-color: #FCEBD9;">
from suncasa.eovsa import eovsa_dspec as ds
from astropy.time import Time
from matplotlib.colors import LogNorm
## Read EOVSA Dynamic Spectrum FITS file <filename>
filename = 'EOVSA_TPall_20170713.fts'
s = ds.get_dspec(filename, doplot=True, cmap='gist_heat', norm=LogNorm(vmax=2.1e3, vmin=40))
## To access the data in the spectrogram object, use
spec = s['spectrogram'] ## (Array of amplitudes in SFU, of size nfreq,ntimes)
fghz = s['spectrum_axis'] ## (Array of frequencies in GHz, of size nfreq)
tim = Time(s['time_axis'], format='mjd') ## (Array of UT times in astropy.time object, of size ntimes)

</pre>

The '''get_dspec''' function is accessible on [https://github.com/suncasa/suncasa-src/blob/master/suncasa/eovsa/eovsa_dspec.py GitHub]. For comprehensive guidance, please refer to suncasa's [https://suncasa-src.readthedocs.io/en/latest/autoapi/suncasa/eovsa/eovsa_dspec/index.html ReadtheDocs page].
[[File:TPSP.jpeg|center|500px]]

The following code will read the spectrogram file in IDL:

<pre style="background-color: #FCEBD9;">
function dspec,filename,doplot=doplot
; Read EOVSA Dynamic Spectrum FITS file <filename> and return a spectrogram object.
; Optionally show an overview plot if doplot switch is set
;
; Usage:
; s = dspec(<filename>) ; Returns spectrogram object
; s = dspec(<filename>,/doplot) ; Plots spectrum and returns spectrogram object
;
; To access the data in the spectrogram object, use
; spec = s.get(/spectrogram) (Array of amplitudes in SFU, of size ntimes, nfreq)
; fghz = s.get(/spectrum_axis) (Array of frequencies in GHz, of size nfreq)
; ut = s.get(/time_axis) (Array of UT times in anytim format, of size ntimes)

default,doplot,0
spec = mrdfits(filename,0)
freq = mrdfits(filename,1)
time = mrdfits(filename,2)
fghz = freq.sfreq
ut = anytim(time)
s = spectrogram(spec,ut,fghz)
if doplot then begin
window,/free,xsiz=1024,ysiz=600
; Find min and max of data from 5% to 95% of sorted array (eliminates outliers)
sarr = sort(spec)
dlim = minmax(spec[sarr[n_elements(sarr)*0.05:n_elements(sarr)*0.95]])
; Set drange with margin factor of 2 on low end and 5 on high end
s.set,drange=dlim*[0.5,5]
loadct,3
s.plot,/log,/xsty,/ysty,ytitle='Frequency [GHz]',charsize=1.5
endif
return,s
end
</pre>
[[File:IDL_TPSP.png|center|500px]]

===Synoptic 6-band Images===
Full disk images at 6 selected frequency bands centered at 1.4, 3.0, 4.5, 6.8, 10.2, and 13.9 GHz are provided once per day, calibrated in brightness temperature. [[File:synoptic_image.jpg| center |400px]]

The EOVSA full disk image FITS files are compressed with the RICE algorithm implemented in the FITS file handling module (astropy.io.fits) in Astropy. EOVSA FITS files are very similar to the compressed SDO/AIA FITS files from JSOC. Popular coding languages can easily read compressed images directly.

In IDL, you can use read_sdo in the ONTOLOGY package, which should be installed by default in SolarSoftWare (SSW), to read compressed EOVSA FITS files. The following code will read the EOVSA image FITS file in SSWIDL:

<pre style="background-color: #FCEBD9;">
read_sdo,'eovsa_20191225.spw11-20.tb.disk.fits',header,data,/UNCOMP_DELETE
index2map,header,data,eomap
plot_map,eomap
</pre>

[[File:eovsa_20191225_image_sswidl.jpg| center |250px]]

In Python, you can use SunPy map module to read EOVAS FITS files. SunPy is an open solar data analysis environment for Python. The installation instruction can be found at [https://sunpy.org/ SunPy official website].
<pre style="background-color: #FCEBD9;">
import matplotlib.pyplot as plt
from sunpy import map as smap
eofile='eovsa_20191225.spw11-20.tb.disk.fits'
eomap = smap.Map(eofile)
eomap.plot()
plt.show()
</pre>
[[File:eovsa_20191225_image_py.jpg| center |250px]]

We have developed a package for EOVSA data processing and analysis:
[https://github.com/suncasa/suncasa SunCASA] A wrapper around [https://casa.nrao.edu/ CASA (the Common Astronomy Software Applications package)] for synthesis imaging and visualizing solar spectral imaging data. CASA is one of the leading software tools for "supporting the data post-processing needs of the next generation of radio astronomical telescopes such as ALMA and VLA", an international effort led by the [https://public.nrao.edu/ National Radio Astronomy Observatory]. The current version of CASA uses Python (2.7) interface. More information about CASA can be found on [https://casa.nrao.edu/ NRAO's CASA website ]. Note, CASA is available ONLY on UNIX-BASED PLATFORMS (and therefore, so is SunCASA). We are developing a new version of SunCASA based on CASA 6 (which offers a modular approach) so that users have the flexibility to build CASA tools and tasks in their Python environment.

Please [http://www.ovsa.njit.edu/wiki/index.php/SunCASA_Installation follow this link] for details regarding the installation of SunCASA on your own machine (only available on Unix-bases OS). This will take you to another page.

EOVSA Data Products

2024-03-29T15:10:45Z

Binchen: /* Level 0.5 - Calibrated visibility data */

=Introduction=
EOVSA observes the full disk of the Sun at all times when the Sun is >10 degrees above the local horizon (season dependent and ranges from 7-12 hours duration centered on 20 UT). EOVSA records data at 451 science frequency channels each second, in four polarization products, as well as additional total flux measurements from each individual antenna. Raw data in the visibility domain are processed through a pipeline processing system to produce images and spectrograms in the time- and frequency-dependent image plane (the block diagram in Figure 1 shows the data flow in the pipeline).
[[File:pipeline_flowchart.jpg|center|600px|EOVSA pipeline block diagram/flow chart ]]

We deliver the radio interferometry data on the following three levels:

=Level 0 - Raw visibility data from the instrument=

As outlined in Figure 1, EOVSA creates raw data products in the left-hand column (labeled Level 0). This includes observations of cosmic sources for phase calibration, and gain and pointing observations required for total power calibration.

==Raw "Interim" Database (IDB) visibility data==
Full-resolution raw "Interim" Database (IDB) visibility data. They are stored in Miriad format, and hence may not be that useful for most people. Be patient after clicking the link--this is a very long list of directories, one for each available date. These data can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/IDB/

==Raw 1-min-averaged visibility data==
This is the same as for the IDB data, except with 1-minute time integration applied. This is typically not useful for flares, but is perfectly fine for imaging active regions and full Sun. These data can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/UDB/

=Level 0.5 - Calibrated visibility data=
After applying calibration and other preliminary processing to the raw (level 0) data, we create the CASA ms’s in the second column in Figure 1 (labeled "level 0.5"). These visibility data are in the Fourier domain of the true images in the plane of the sky and are not immediately ready for spectral imaging analysis yet. However, they have all of the required content to produce images and spectrogram data in standard FITS format (level 1.0). We provide a set of standard ms’s for each day (red boxes in Figure 1), for use by researchers who know how to deal with visibility data. These data are more suitable for experienced users to exploit the full potential of EOVSA data, such as spatially resolved spectral analysis. Processing these data requires CASA or sunCASA (https://github.com/suncasa/suncasa-src). Please refer to our tutorial at [[EOVSA_Data_Analysis_Tutorial_2022]].

==Calibrated full-resolution visibility data for flare events==
Calibrated and self-calibrated visibility data for flare events (purple boxes in Figure 1) will typically be available within 7 days after they are taken. They will be released at our flare list site soon: https://ovsa.njit.edu/flarelist

==Self-calibrated 1-min-averaged visibility data==
EOVSA 1-min averaged visibility data in CASA ms format can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/UDBms_slfcaled

=Level 1.0 - Images and spectrogram data in standard FITS format =

Level 1.0 data are for users who prefer to work with spectrogram (frequency-time) and image data directly, which are also outputs of the pipeline system shown in Figure 1 (orange boxes). They are perfectly suitable to be used as context data for comparison with other multi-wavelength observations but are not (yet) intended for quantitative spatially resolved spectral analysis.

Spectrograms are provided as standard FITS tables containing the frequency list, list of times, and data in both total power (TP) and a sum of amplitudes over intermediate-length baselines (cross power or XP). Likewise, image data products are in FITS format with standard keywords and are converted into the Helioprojective Cartesian coordinate system compatible with the World Coordinate System (WCS) convention, along with correct registration for the spatial, spectral, and temporal coordinates. Both the spectrogram and image data products are calibrated and have physical radio intensity units (sfu for spectrograms and brightness temperature for radio images).

We provide the following data products:
* Synoptic products:
** '''All-day spectrograms''':
** '''All-day synoptic images''': Full disk images at 6 selected frequency bands centered at 1.4, 3.0, 4.5, 6.8, 10.2, and 13.9 GHz are produced once per day utilizing the earth-rotation synthesis, calibrated in brightness temperature. This is because EOVSA has a limited number of baselines and we need a long integration to fill up the uv domain in order to make full-disk images.
* Event-based products:
** '''Flare spectrograms''': These are full time and frequency resolution spectrograms produced from the median of calibrated cross-power visibilities in FITS format, cropped to cover the flare duration. Preflare background is also subtracted. Compared to total-power spectrograms, these spectrograms have the advantage of revealing details of the flare evolution by "filtering out" the large-scale, continuous background from the visibilities. Note that for certain flares that have a large source size, the flux can be lower than its true values (as a fraction of the flux will be "resolved out").
** '''Pipeline-produced spectral images''': We also have a semi-automated flare imaging pipeline to produce calibrated (and self-calibrated) images at 12-s cadence at up to 10 frequency bands. They are saved in standard FITS format and have been registered into Helioprojective coordinates. They can be read by SSWIDL or astropy/sunpy. These data have already been calibrated to physical units and are usually good to be compared with context data. But please be cautious when using them for quantitative spectral analysis.

{| class="wikitable"
|+ Summary of EOVSA Level 1 Data Products
|-
! scope="col"| Category
! scope="col"| Data Product
! scope="col"| Naming Convention
! scope="col"| Download Link
|-
! rowspan="2" | Synoptic Spectrograms
| All-day TP Spectrograms
| EOVSA_TPall_yyyymmdd.fts
!rowspan="9" | https://ovsa.njit.edu/browser
|-
| All-day XP Spectrograms
| EOVSA_XPall_yyyymmdd.fts
|-
! rowspan="7" | Synoptic Images
|-
| Synoptic 1.4 GHz images
| eovsa_yyyymmdd.spw00-01.tb.disk.fits
|-
| Synoptic 3.0 GHz images
| eovsa_yyyymmdd.spw02-05.tb.disk.fits
|-
| Synoptic 4.5 GHz images
| eovsa_yyyymmdd.spw06-10.tb.disk.fits
|-
| Synoptic 6.8 GHz images
| eovsa_yyyymmdd.spw11-20.tb.disk.fits
|-
| Synoptic 10.2 GHz images
| eovsa_yyyymmdd.spw21-30.tb.disk.fits
|-
| Synoptic 13.9 GHz images
| eovsa_yyyymmdd.spw31-43.tb.disk.fits
|-
! rowspan="1" | Flare Spectrograms
| Full-resolution cross-power Spectrogram
| eovsa.spec.flare_id_YYYYMMDDHHMMSS.fits
!rowspan="2" | https://ovsa.njit.edu/flarelist
|-
! rowspan="1" | Flare Spectral Images
| Pipeline-produced spectral images
| eovsa.lev1_mbd_12s.YYYY-MM-DDTHHMMSSZ.image.fits
|-
|}

==Browsing and Downloading level 1 data==
[[File:eovsa_browser.jpg|right|thumb|EOVSA Browser]]
[[file:EOVSA_flarelist.jpg|right|thumb|EOVSA Flare List]]
===Synoptic level 1 data===
EOVSA Level 1 synoptic data products can be retrieved with the following steps:
* Go to [http://ovsa.njit.edu/browser/ EOVSA browser] page.
* Browse to the date of interest.
* Click "synoptic fits" button next to the calendar tool.
* Select the data product based on the names listed in the table above.

===Flare level 1 data===
EOVSA flare list with spectrograms and spectral images can be queried and downloaded at https://ovsa.njit.edu/flarelist. Users can use the top box to select a time range of interest and query our flare list. The results are displayed in the dropdown box. An interactive plot of the flare light curves will be shown at the bottom of the page once an event is highlighted (by clicking on the flare ID). Quicklook plots and FITS files of the spectrograms and flare movies can be accessed by clicking the icons in each flare record.

==Reading and Using level 1 data==
===Introduction===
All our level 1 data products are in FITS format. All the images have standard, WCS-compatible coordinates. Users can use their favorite method to read these files. In the following, we provide minimal examples to read them with Astropy and Sunpy.

===Event-Based Data Products===
* An example of how to read and plot the flare spectrograms and images in Python (with Astropy and SunPy) can be accessed at [https://colab.research.google.com/drive/1Y3ONWCxLPYvWda5_LqFNxafJtwZDNJBD?usp=sharing#scrollTo=ueiMoHbdxfo- this Google Colab Jupyter notebook].
* We are working on an example with SSWIDL and will release it soon.

===Synoptic Data Products===

===All-day Spectrograms===
To read a spectrogram file in Python using the suncasa library:

<pre style="background-color: #FCEBD9;">
from suncasa.eovsa import eovsa_dspec as ds
from astropy.time import Time
from matplotlib.colors import LogNorm
## Read EOVSA Dynamic Spectrum FITS file <filename>
filename = 'EOVSA_TPall_20170713.fts'
s = ds.get_dspec(filename, doplot=True, cmap='gist_heat', norm=LogNorm(vmax=2.1e3, vmin=40))
## To access the data in the spectrogram object, use
spec = s['spectrogram'] ## (Array of amplitudes in SFU, of size nfreq,ntimes)
fghz = s['spectrum_axis'] ## (Array of frequencies in GHz, of size nfreq)
tim = Time(s['time_axis'], format='mjd') ## (Array of UT times in astropy.time object, of size ntimes)

</pre>

The '''get_dspec''' function is accessible on [https://github.com/suncasa/suncasa-src/blob/master/suncasa/eovsa/eovsa_dspec.py GitHub]. For comprehensive guidance, please refer to suncasa's [https://suncasa-src.readthedocs.io/en/latest/autoapi/suncasa/eovsa/eovsa_dspec/index.html ReadtheDocs page].
[[File:TPSP.jpeg|center|500px]]

The following code will read the spectrogram file in IDL:

<pre style="background-color: #FCEBD9;">
function dspec,filename,doplot=doplot
; Read EOVSA Dynamic Spectrum FITS file <filename> and return a spectrogram object.
; Optionally show an overview plot if doplot switch is set
;
; Usage:
; s = dspec(<filename>) ; Returns spectrogram object
; s = dspec(<filename>,/doplot) ; Plots spectrum and returns spectrogram object
;
; To access the data in the spectrogram object, use
; spec = s.get(/spectrogram) (Array of amplitudes in SFU, of size ntimes, nfreq)
; fghz = s.get(/spectrum_axis) (Array of frequencies in GHz, of size nfreq)
; ut = s.get(/time_axis) (Array of UT times in anytim format, of size ntimes)

default,doplot,0
spec = mrdfits(filename,0)
freq = mrdfits(filename,1)
time = mrdfits(filename,2)
fghz = freq.sfreq
ut = anytim(time)
s = spectrogram(spec,ut,fghz)
if doplot then begin
window,/free,xsiz=1024,ysiz=600
; Find min and max of data from 5% to 95% of sorted array (eliminates outliers)
sarr = sort(spec)
dlim = minmax(spec[sarr[n_elements(sarr)*0.05:n_elements(sarr)*0.95]])
; Set drange with margin factor of 2 on low end and 5 on high end
s.set,drange=dlim*[0.5,5]
loadct,3
s.plot,/log,/xsty,/ysty,ytitle='Frequency [GHz]',charsize=1.5
endif
return,s
end
</pre>
[[File:IDL_TPSP.png|center|500px]]

===Synoptic 6-band Images===
Full disk images at 6 selected frequency bands centered at 1.4, 3.0, 4.5, 6.8, 10.2, and 13.9 GHz are provided once per day, calibrated in brightness temperature. [[File:synoptic_image.jpg| center |400px]]

The EOVSA full disk image FITS files are compressed with the RICE algorithm implemented in the FITS file handling module (astropy.io.fits) in Astropy. EOVSA FITS files are very similar to the compressed SDO/AIA FITS files from JSOC. Popular coding languages can easily read compressed images directly.

In IDL, you can use read_sdo in the ONTOLOGY package, which should be installed by default in SolarSoftWare (SSW), to read compressed EOVSA FITS files. The following code will read the EOVSA image FITS file in SSWIDL:

<pre style="background-color: #FCEBD9;">
read_sdo,'eovsa_20191225.spw11-20.tb.disk.fits',header,data,/UNCOMP_DELETE
index2map,header,data,eomap
plot_map,eomap
</pre>

[[File:eovsa_20191225_image_sswidl.jpg| center |250px]]

In Python, you can use SunPy map module to read EOVAS FITS files. SunPy is an open solar data analysis environment for Python. The installation instruction can be found at [https://sunpy.org/ SunPy official website].
<pre style="background-color: #FCEBD9;">
import matplotlib.pyplot as plt
from sunpy import map as smap
eofile='eovsa_20191225.spw11-20.tb.disk.fits'
eomap = smap.Map(eofile)
eomap.plot()
plt.show()
</pre>
[[File:eovsa_20191225_image_py.jpg| center |250px]]

We have developed a package for EOVSA data processing and analysis:
[https://github.com/suncasa/suncasa SunCASA] A wrapper around [https://casa.nrao.edu/ CASA (the Common Astronomy Software Applications package)] for synthesis imaging and visualizing solar spectral imaging data. CASA is one of the leading software tools for "supporting the data post-processing needs of the next generation of radio astronomical telescopes such as ALMA and VLA", an international effort led by the [https://public.nrao.edu/ National Radio Astronomy Observatory]. The current version of CASA uses Python (2.7) interface. More information about CASA can be found on [https://casa.nrao.edu/ NRAO's CASA website ]. Note, CASA is available ONLY on UNIX-BASED PLATFORMS (and therefore, so is SunCASA). We are developing a new version of SunCASA based on CASA 6 (which offers a modular approach) so that users have the flexibility to build CASA tools and tasks in their Python environment.

Please [http://www.ovsa.njit.edu/wiki/index.php/SunCASA_Installation follow this link] for details regarding the installation of SunCASA on your own machine (only available on Unix-bases OS). This will take you to another page.

EOVSA Data Products

2024-03-29T15:10:22Z

Binchen: /* Level 0.5 - Calibrated visibility data */

=Introduction=
EOVSA observes the full disk of the Sun at all times when the Sun is >10 degrees above the local horizon (season dependent and ranges from 7-12 hours duration centered on 20 UT). EOVSA records data at 451 science frequency channels each second, in four polarization products, as well as additional total flux measurements from each individual antenna. Raw data in the visibility domain are processed through a pipeline processing system to produce images and spectrograms in the time- and frequency-dependent image plane (the block diagram in Figure 1 shows the data flow in the pipeline).
[[File:pipeline_flowchart.jpg|center|600px|EOVSA pipeline block diagram/flow chart ]]

We deliver the radio interferometry data on the following three levels:

=Level 0 - Raw visibility data from the instrument=

As outlined in Figure 1, EOVSA creates raw data products in the left-hand column (labeled Level 0). This includes observations of cosmic sources for phase calibration, and gain and pointing observations required for total power calibration.

==Raw "Interim" Database (IDB) visibility data==
Full-resolution raw "Interim" Database (IDB) visibility data. They are stored in Miriad format, and hence may not be that useful for most people. Be patient after clicking the link--this is a very long list of directories, one for each available date. These data can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/IDB/

==Raw 1-min-averaged visibility data==
This is the same as for the IDB data, except with 1-minute time integration applied. This is typically not useful for flares, but is perfectly fine for imaging active regions and full Sun. These data can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/UDB/

=Level 0.5 - Calibrated visibility data=
After applying calibration and other preliminary processing to the raw (level 0) data, we create the CASA ms’s in the second column in Figure 1 (labeled "level 0.5"). These visibility data are in the Fourier domain of the true images in the plane of the sky and are not immediately ready for spectral imaging analysis yet. However, they have all of the required content to produce images and spectrogram data in standard FITS format (level 1.0). We provide a set of standard ms’s for each day (red boxes in Figure 1), for use by researchers who know how to deal with visibility data. These data are more suitable for experienced users to exploit the full potential of EOVSA data, such as spatially resolved spectral analysis. Processing these data requires CASA or sunCASA (https://github.com/suncasa/suncasa-src). Please refer to our tutorial at [[EOVSA_Data_Analysis_Tutorial_2022]]

==Calibrated full-resolution visibility data for flare events==
Calibrated and self-calibrated visibility data for flare events (purple boxes in Figure 1) will typically be available within 7 days after they are taken. They will be released at our flare list site soon: https://ovsa.njit.edu/flarelist

==Self-calibrated 1-min-averaged visibility data==
EOVSA 1-min averaged visibility data in CASA ms format can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/UDBms_slfcaled

=Level 1.0 - Images and spectrogram data in standard FITS format =

Level 1.0 data are for users who prefer to work with spectrogram (frequency-time) and image data directly, which are also outputs of the pipeline system shown in Figure 1 (orange boxes). They are perfectly suitable to be used as context data for comparison with other multi-wavelength observations but are not (yet) intended for quantitative spatially resolved spectral analysis.

Spectrograms are provided as standard FITS tables containing the frequency list, list of times, and data in both total power (TP) and a sum of amplitudes over intermediate-length baselines (cross power or XP). Likewise, image data products are in FITS format with standard keywords and are converted into the Helioprojective Cartesian coordinate system compatible with the World Coordinate System (WCS) convention, along with correct registration for the spatial, spectral, and temporal coordinates. Both the spectrogram and image data products are calibrated and have physical radio intensity units (sfu for spectrograms and brightness temperature for radio images).

We provide the following data products:
* Synoptic products:
** '''All-day spectrograms''':
** '''All-day synoptic images''': Full disk images at 6 selected frequency bands centered at 1.4, 3.0, 4.5, 6.8, 10.2, and 13.9 GHz are produced once per day utilizing the earth-rotation synthesis, calibrated in brightness temperature. This is because EOVSA has a limited number of baselines and we need a long integration to fill up the uv domain in order to make full-disk images.
* Event-based products:
** '''Flare spectrograms''': These are full time and frequency resolution spectrograms produced from the median of calibrated cross-power visibilities in FITS format, cropped to cover the flare duration. Preflare background is also subtracted. Compared to total-power spectrograms, these spectrograms have the advantage of revealing details of the flare evolution by "filtering out" the large-scale, continuous background from the visibilities. Note that for certain flares that have a large source size, the flux can be lower than its true values (as a fraction of the flux will be "resolved out").
** '''Pipeline-produced spectral images''': We also have a semi-automated flare imaging pipeline to produce calibrated (and self-calibrated) images at 12-s cadence at up to 10 frequency bands. They are saved in standard FITS format and have been registered into Helioprojective coordinates. They can be read by SSWIDL or astropy/sunpy. These data have already been calibrated to physical units and are usually good to be compared with context data. But please be cautious when using them for quantitative spectral analysis.

{| class="wikitable"
|+ Summary of EOVSA Level 1 Data Products
|-
! scope="col"| Category
! scope="col"| Data Product
! scope="col"| Naming Convention
! scope="col"| Download Link
|-
! rowspan="2" | Synoptic Spectrograms
| All-day TP Spectrograms
| EOVSA_TPall_yyyymmdd.fts
!rowspan="9" | https://ovsa.njit.edu/browser
|-
| All-day XP Spectrograms
| EOVSA_XPall_yyyymmdd.fts
|-
! rowspan="7" | Synoptic Images
|-
| Synoptic 1.4 GHz images
| eovsa_yyyymmdd.spw00-01.tb.disk.fits
|-
| Synoptic 3.0 GHz images
| eovsa_yyyymmdd.spw02-05.tb.disk.fits
|-
| Synoptic 4.5 GHz images
| eovsa_yyyymmdd.spw06-10.tb.disk.fits
|-
| Synoptic 6.8 GHz images
| eovsa_yyyymmdd.spw11-20.tb.disk.fits
|-
| Synoptic 10.2 GHz images
| eovsa_yyyymmdd.spw21-30.tb.disk.fits
|-
| Synoptic 13.9 GHz images
| eovsa_yyyymmdd.spw31-43.tb.disk.fits
|-
! rowspan="1" | Flare Spectrograms
| Full-resolution cross-power Spectrogram
| eovsa.spec.flare_id_YYYYMMDDHHMMSS.fits
!rowspan="2" | https://ovsa.njit.edu/flarelist
|-
! rowspan="1" | Flare Spectral Images
| Pipeline-produced spectral images
| eovsa.lev1_mbd_12s.YYYY-MM-DDTHHMMSSZ.image.fits
|-
|}

==Browsing and Downloading level 1 data==
[[File:eovsa_browser.jpg|right|thumb|EOVSA Browser]]
[[file:EOVSA_flarelist.jpg|right|thumb|EOVSA Flare List]]
===Synoptic level 1 data===
EOVSA Level 1 synoptic data products can be retrieved with the following steps:
* Go to [http://ovsa.njit.edu/browser/ EOVSA browser] page.
* Browse to the date of interest.
* Click "synoptic fits" button next to the calendar tool.
* Select the data product based on the names listed in the table above.

===Flare level 1 data===
EOVSA flare list with spectrograms and spectral images can be queried and downloaded at https://ovsa.njit.edu/flarelist. Users can use the top box to select a time range of interest and query our flare list. The results are displayed in the dropdown box. An interactive plot of the flare light curves will be shown at the bottom of the page once an event is highlighted (by clicking on the flare ID). Quicklook plots and FITS files of the spectrograms and flare movies can be accessed by clicking the icons in each flare record.

==Reading and Using level 1 data==
===Introduction===
All our level 1 data products are in FITS format. All the images have standard, WCS-compatible coordinates. Users can use their favorite method to read these files. In the following, we provide minimal examples to read them with Astropy and Sunpy.

===Event-Based Data Products===
* An example of how to read and plot the flare spectrograms and images in Python (with Astropy and SunPy) can be accessed at [https://colab.research.google.com/drive/1Y3ONWCxLPYvWda5_LqFNxafJtwZDNJBD?usp=sharing#scrollTo=ueiMoHbdxfo- this Google Colab Jupyter notebook].
* We are working on an example with SSWIDL and will release it soon.

===Synoptic Data Products===

===All-day Spectrograms===
To read a spectrogram file in Python using the suncasa library:

<pre style="background-color: #FCEBD9;">
from suncasa.eovsa import eovsa_dspec as ds
from astropy.time import Time
from matplotlib.colors import LogNorm
## Read EOVSA Dynamic Spectrum FITS file <filename>
filename = 'EOVSA_TPall_20170713.fts'
s = ds.get_dspec(filename, doplot=True, cmap='gist_heat', norm=LogNorm(vmax=2.1e3, vmin=40))
## To access the data in the spectrogram object, use
spec = s['spectrogram'] ## (Array of amplitudes in SFU, of size nfreq,ntimes)
fghz = s['spectrum_axis'] ## (Array of frequencies in GHz, of size nfreq)
tim = Time(s['time_axis'], format='mjd') ## (Array of UT times in astropy.time object, of size ntimes)

</pre>

The '''get_dspec''' function is accessible on [https://github.com/suncasa/suncasa-src/blob/master/suncasa/eovsa/eovsa_dspec.py GitHub]. For comprehensive guidance, please refer to suncasa's [https://suncasa-src.readthedocs.io/en/latest/autoapi/suncasa/eovsa/eovsa_dspec/index.html ReadtheDocs page].
[[File:TPSP.jpeg|center|500px]]

The following code will read the spectrogram file in IDL:

<pre style="background-color: #FCEBD9;">
function dspec,filename,doplot=doplot
; Read EOVSA Dynamic Spectrum FITS file <filename> and return a spectrogram object.
; Optionally show an overview plot if doplot switch is set
;
; Usage:
; s = dspec(<filename>) ; Returns spectrogram object
; s = dspec(<filename>,/doplot) ; Plots spectrum and returns spectrogram object
;
; To access the data in the spectrogram object, use
; spec = s.get(/spectrogram) (Array of amplitudes in SFU, of size ntimes, nfreq)
; fghz = s.get(/spectrum_axis) (Array of frequencies in GHz, of size nfreq)
; ut = s.get(/time_axis) (Array of UT times in anytim format, of size ntimes)

default,doplot,0
spec = mrdfits(filename,0)
freq = mrdfits(filename,1)
time = mrdfits(filename,2)
fghz = freq.sfreq
ut = anytim(time)
s = spectrogram(spec,ut,fghz)
if doplot then begin
window,/free,xsiz=1024,ysiz=600
; Find min and max of data from 5% to 95% of sorted array (eliminates outliers)
sarr = sort(spec)
dlim = minmax(spec[sarr[n_elements(sarr)*0.05:n_elements(sarr)*0.95]])
; Set drange with margin factor of 2 on low end and 5 on high end
s.set,drange=dlim*[0.5,5]
loadct,3
s.plot,/log,/xsty,/ysty,ytitle='Frequency [GHz]',charsize=1.5
endif
return,s
end
</pre>
[[File:IDL_TPSP.png|center|500px]]

===Synoptic 6-band Images===
Full disk images at 6 selected frequency bands centered at 1.4, 3.0, 4.5, 6.8, 10.2, and 13.9 GHz are provided once per day, calibrated in brightness temperature. [[File:synoptic_image.jpg| center |400px]]

The EOVSA full disk image FITS files are compressed with the RICE algorithm implemented in the FITS file handling module (astropy.io.fits) in Astropy. EOVSA FITS files are very similar to the compressed SDO/AIA FITS files from JSOC. Popular coding languages can easily read compressed images directly.

In IDL, you can use read_sdo in the ONTOLOGY package, which should be installed by default in SolarSoftWare (SSW), to read compressed EOVSA FITS files. The following code will read the EOVSA image FITS file in SSWIDL:

<pre style="background-color: #FCEBD9;">
read_sdo,'eovsa_20191225.spw11-20.tb.disk.fits',header,data,/UNCOMP_DELETE
index2map,header,data,eomap
plot_map,eomap
</pre>

[[File:eovsa_20191225_image_sswidl.jpg| center |250px]]

In Python, you can use SunPy map module to read EOVAS FITS files. SunPy is an open solar data analysis environment for Python. The installation instruction can be found at [https://sunpy.org/ SunPy official website].
<pre style="background-color: #FCEBD9;">
import matplotlib.pyplot as plt
from sunpy import map as smap
eofile='eovsa_20191225.spw11-20.tb.disk.fits'
eomap = smap.Map(eofile)
eomap.plot()
plt.show()
</pre>
[[File:eovsa_20191225_image_py.jpg| center |250px]]

We have developed a package for EOVSA data processing and analysis:
[https://github.com/suncasa/suncasa SunCASA] A wrapper around [https://casa.nrao.edu/ CASA (the Common Astronomy Software Applications package)] for synthesis imaging and visualizing solar spectral imaging data. CASA is one of the leading software tools for "supporting the data post-processing needs of the next generation of radio astronomical telescopes such as ALMA and VLA", an international effort led by the [https://public.nrao.edu/ National Radio Astronomy Observatory]. The current version of CASA uses Python (2.7) interface. More information about CASA can be found on [https://casa.nrao.edu/ NRAO's CASA website ]. Note, CASA is available ONLY on UNIX-BASED PLATFORMS (and therefore, so is SunCASA). We are developing a new version of SunCASA based on CASA 6 (which offers a modular approach) so that users have the flexibility to build CASA tools and tasks in their Python environment.

Please [http://www.ovsa.njit.edu/wiki/index.php/SunCASA_Installation follow this link] for details regarding the installation of SunCASA on your own machine (only available on Unix-bases OS). This will take you to another page.

EOVSA Data Products

2024-03-29T15:08:35Z

Binchen: /* Level 1.0 - Images and spectrogram data in standard FITS format */

=Introduction=
EOVSA observes the full disk of the Sun at all times when the Sun is >10 degrees above the local horizon (season dependent and ranges from 7-12 hours duration centered on 20 UT). EOVSA records data at 451 science frequency channels each second, in four polarization products, as well as additional total flux measurements from each individual antenna. Raw data in the visibility domain are processed through a pipeline processing system to produce images and spectrograms in the time- and frequency-dependent image plane (the block diagram in Figure 1 shows the data flow in the pipeline).
[[File:pipeline_flowchart.jpg|center|600px|EOVSA pipeline block diagram/flow chart ]]

We deliver the radio interferometry data on the following three levels:

=Level 0 - Raw visibility data from the instrument=

As outlined in Figure 1, EOVSA creates raw data products in the left-hand column (labeled Level 0). This includes observations of cosmic sources for phase calibration, and gain and pointing observations required for total power calibration.

==Raw "Interim" Database (IDB) visibility data==
Full-resolution raw "Interim" Database (IDB) visibility data. They are stored in Miriad format, and hence may not be that useful for most people. Be patient after clicking the link--this is a very long list of directories, one for each available date. These data can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/IDB/

==Raw 1-min-averaged visibility data==
This is the same as for the IDB data, except with 1-minute time integration applied. This is typically not useful for flares, but is perfectly fine for imaging active regions and full Sun. These data can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/UDB/

=Level 0.5 - Calibrated visibility data=
After applying calibration and other preliminary processing to the raw (level 0) data, we create the CASA ms’s in the second column in Figure 1 (labeled "level 0.5"). These visibility data are in the Fourier domain of the true images in the plane of the sky and are not immediately ready for spectral imaging analysis yet. However, they have all of the required content to produce images and spectrogram data in standard FITS format (level 1.0). We provide a set of standard ms’s for each day (red boxes in Figure 1), for use by researchers who know how to deal with visibility data. These data are more suitable for experienced users to exploit the full potential of EOVSA data, such as spatially resolved spectral analysis. Processing these data requires CASA or sunCASA (https://github.com/suncasa/suncasa-src).

==Calibrated full-resolution visibility data for flare events==
Calibrated and self-calibrated visibility data for flare events (purple boxes in Figure 1) will typically be available within 7 days after they are taken. They will be released at our flare list site soon: https://ovsa.njit.edu/flarelist

==Self-calibrated 1-min-averaged visibility data==
EOVSA 1-min averaged visibility data in CASA ms format can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/UDBms_slfcaled

=Level 1.0 - Images and spectrogram data in standard FITS format =

Level 1.0 data are for users who prefer to work with spectrogram (frequency-time) and image data directly, which are also outputs of the pipeline system shown in Figure 1 (orange boxes). They are perfectly suitable to be used as context data for comparison with other multi-wavelength observations but are not (yet) intended for quantitative spatially resolved spectral analysis.

Spectrograms are provided as standard FITS tables containing the frequency list, list of times, and data in both total power (TP) and a sum of amplitudes over intermediate-length baselines (cross power or XP). Likewise, image data products are in FITS format with standard keywords and are converted into the Helioprojective Cartesian coordinate system compatible with the World Coordinate System (WCS) convention, along with correct registration for the spatial, spectral, and temporal coordinates. Both the spectrogram and image data products are calibrated and have physical radio intensity units (sfu for spectrograms and brightness temperature for radio images).

We provide the following data products:
* Synoptic products:
** '''All-day spectrograms''':
** '''All-day synoptic images''': Full disk images at 6 selected frequency bands centered at 1.4, 3.0, 4.5, 6.8, 10.2, and 13.9 GHz are produced once per day utilizing the earth-rotation synthesis, calibrated in brightness temperature. This is because EOVSA has a limited number of baselines and we need a long integration to fill up the uv domain in order to make full-disk images.
* Event-based products:
** '''Flare spectrograms''': These are full time and frequency resolution spectrograms produced from the median of calibrated cross-power visibilities in FITS format, cropped to cover the flare duration. Preflare background is also subtracted. Compared to total-power spectrograms, these spectrograms have the advantage of revealing details of the flare evolution by "filtering out" the large-scale, continuous background from the visibilities. Note that for certain flares that have a large source size, the flux can be lower than its true values (as a fraction of the flux will be "resolved out").
** '''Pipeline-produced spectral images''': We also have a semi-automated flare imaging pipeline to produce calibrated (and self-calibrated) images at 12-s cadence at up to 10 frequency bands. They are saved in standard FITS format and have been registered into Helioprojective coordinates. They can be read by SSWIDL or astropy/sunpy. These data have already been calibrated to physical units and are usually good to be compared with context data. But please be cautious when using them for quantitative spectral analysis.

{| class="wikitable"
|+ Summary of EOVSA Level 1 Data Products
|-
! scope="col"| Category
! scope="col"| Data Product
! scope="col"| Naming Convention
! scope="col"| Download Link
|-
! rowspan="2" | Synoptic Spectrograms
| All-day TP Spectrograms
| EOVSA_TPall_yyyymmdd.fts
!rowspan="9" | https://ovsa.njit.edu/browser
|-
| All-day XP Spectrograms
| EOVSA_XPall_yyyymmdd.fts
|-
! rowspan="7" | Synoptic Images
|-
| Synoptic 1.4 GHz images
| eovsa_yyyymmdd.spw00-01.tb.disk.fits
|-
| Synoptic 3.0 GHz images
| eovsa_yyyymmdd.spw02-05.tb.disk.fits
|-
| Synoptic 4.5 GHz images
| eovsa_yyyymmdd.spw06-10.tb.disk.fits
|-
| Synoptic 6.8 GHz images
| eovsa_yyyymmdd.spw11-20.tb.disk.fits
|-
| Synoptic 10.2 GHz images
| eovsa_yyyymmdd.spw21-30.tb.disk.fits
|-
| Synoptic 13.9 GHz images
| eovsa_yyyymmdd.spw31-43.tb.disk.fits
|-
! rowspan="1" | Flare Spectrograms
| Full-resolution cross-power Spectrogram
| eovsa.spec.flare_id_YYYYMMDDHHMMSS.fits
!rowspan="2" | https://ovsa.njit.edu/flarelist
|-
! rowspan="1" | Flare Spectral Images
| Pipeline-produced spectral images
| eovsa.lev1_mbd_12s.YYYY-MM-DDTHHMMSSZ.image.fits
|-
|}

==Browsing and Downloading level 1 data==
[[File:eovsa_browser.jpg|right|thumb|EOVSA Browser]]
[[file:EOVSA_flarelist.jpg|right|thumb|EOVSA Flare List]]
===Synoptic level 1 data===
EOVSA Level 1 synoptic data products can be retrieved with the following steps:
* Go to [http://ovsa.njit.edu/browser/ EOVSA browser] page.
* Browse to the date of interest.
* Click "synoptic fits" button next to the calendar tool.
* Select the data product based on the names listed in the table above.

===Flare level 1 data===
EOVSA flare list with spectrograms and spectral images can be queried and downloaded at https://ovsa.njit.edu/flarelist. Users can use the top box to select a time range of interest and query our flare list. The results are displayed in the dropdown box. An interactive plot of the flare light curves will be shown at the bottom of the page once an event is highlighted (by clicking on the flare ID). Quicklook plots and FITS files of the spectrograms and flare movies can be accessed by clicking the icons in each flare record.

==Reading and Using level 1 data==
===Introduction===
All our level 1 data products are in FITS format. All the images have standard, WCS-compatible coordinates. Users can use their favorite method to read these files. In the following, we provide minimal examples to read them with Astropy and Sunpy.

===Event-Based Data Products===
* An example of how to read and plot the flare spectrograms and images in Python (with Astropy and SunPy) can be accessed at [https://colab.research.google.com/drive/1Y3ONWCxLPYvWda5_LqFNxafJtwZDNJBD?usp=sharing#scrollTo=ueiMoHbdxfo- this Google Colab Jupyter notebook].
* We are working on an example with SSWIDL and will release it soon.

===Synoptic Data Products===

===All-day Spectrograms===
To read a spectrogram file in Python using the suncasa library:

<pre style="background-color: #FCEBD9;">
from suncasa.eovsa import eovsa_dspec as ds
from astropy.time import Time
from matplotlib.colors import LogNorm
## Read EOVSA Dynamic Spectrum FITS file <filename>
filename = 'EOVSA_TPall_20170713.fts'
s = ds.get_dspec(filename, doplot=True, cmap='gist_heat', norm=LogNorm(vmax=2.1e3, vmin=40))
## To access the data in the spectrogram object, use
spec = s['spectrogram'] ## (Array of amplitudes in SFU, of size nfreq,ntimes)
fghz = s['spectrum_axis'] ## (Array of frequencies in GHz, of size nfreq)
tim = Time(s['time_axis'], format='mjd') ## (Array of UT times in astropy.time object, of size ntimes)

</pre>

The '''get_dspec''' function is accessible on [https://github.com/suncasa/suncasa-src/blob/master/suncasa/eovsa/eovsa_dspec.py GitHub]. For comprehensive guidance, please refer to suncasa's [https://suncasa-src.readthedocs.io/en/latest/autoapi/suncasa/eovsa/eovsa_dspec/index.html ReadtheDocs page].
[[File:TPSP.jpeg|center|500px]]

The following code will read the spectrogram file in IDL:

<pre style="background-color: #FCEBD9;">
function dspec,filename,doplot=doplot
; Read EOVSA Dynamic Spectrum FITS file <filename> and return a spectrogram object.
; Optionally show an overview plot if doplot switch is set
;
; Usage:
; s = dspec(<filename>) ; Returns spectrogram object
; s = dspec(<filename>,/doplot) ; Plots spectrum and returns spectrogram object
;
; To access the data in the spectrogram object, use
; spec = s.get(/spectrogram) (Array of amplitudes in SFU, of size ntimes, nfreq)
; fghz = s.get(/spectrum_axis) (Array of frequencies in GHz, of size nfreq)
; ut = s.get(/time_axis) (Array of UT times in anytim format, of size ntimes)

default,doplot,0
spec = mrdfits(filename,0)
freq = mrdfits(filename,1)
time = mrdfits(filename,2)
fghz = freq.sfreq
ut = anytim(time)
s = spectrogram(spec,ut,fghz)
if doplot then begin
window,/free,xsiz=1024,ysiz=600
; Find min and max of data from 5% to 95% of sorted array (eliminates outliers)
sarr = sort(spec)
dlim = minmax(spec[sarr[n_elements(sarr)*0.05:n_elements(sarr)*0.95]])
; Set drange with margin factor of 2 on low end and 5 on high end
s.set,drange=dlim*[0.5,5]
loadct,3
s.plot,/log,/xsty,/ysty,ytitle='Frequency [GHz]',charsize=1.5
endif
return,s
end
</pre>
[[File:IDL_TPSP.png|center|500px]]

===Synoptic 6-band Images===
Full disk images at 6 selected frequency bands centered at 1.4, 3.0, 4.5, 6.8, 10.2, and 13.9 GHz are provided once per day, calibrated in brightness temperature. [[File:synoptic_image.jpg| center |400px]]

The EOVSA full disk image FITS files are compressed with the RICE algorithm implemented in the FITS file handling module (astropy.io.fits) in Astropy. EOVSA FITS files are very similar to the compressed SDO/AIA FITS files from JSOC. Popular coding languages can easily read compressed images directly.

In IDL, you can use read_sdo in the ONTOLOGY package, which should be installed by default in SolarSoftWare (SSW), to read compressed EOVSA FITS files. The following code will read the EOVSA image FITS file in SSWIDL:

<pre style="background-color: #FCEBD9;">
read_sdo,'eovsa_20191225.spw11-20.tb.disk.fits',header,data,/UNCOMP_DELETE
index2map,header,data,eomap
plot_map,eomap
</pre>

[[File:eovsa_20191225_image_sswidl.jpg| center |250px]]

In Python, you can use SunPy map module to read EOVAS FITS files. SunPy is an open solar data analysis environment for Python. The installation instruction can be found at [https://sunpy.org/ SunPy official website].
<pre style="background-color: #FCEBD9;">
import matplotlib.pyplot as plt
from sunpy import map as smap
eofile='eovsa_20191225.spw11-20.tb.disk.fits'
eomap = smap.Map(eofile)
eomap.plot()
plt.show()
</pre>
[[File:eovsa_20191225_image_py.jpg| center |250px]]

We have developed a package for EOVSA data processing and analysis:
[https://github.com/suncasa/suncasa SunCASA] A wrapper around [https://casa.nrao.edu/ CASA (the Common Astronomy Software Applications package)] for synthesis imaging and visualizing solar spectral imaging data. CASA is one of the leading software tools for "supporting the data post-processing needs of the next generation of radio astronomical telescopes such as ALMA and VLA", an international effort led by the [https://public.nrao.edu/ National Radio Astronomy Observatory]. The current version of CASA uses Python (2.7) interface. More information about CASA can be found on [https://casa.nrao.edu/ NRAO's CASA website ]. Note, CASA is available ONLY on UNIX-BASED PLATFORMS (and therefore, so is SunCASA). We are developing a new version of SunCASA based on CASA 6 (which offers a modular approach) so that users have the flexibility to build CASA tools and tasks in their Python environment.

Please [http://www.ovsa.njit.edu/wiki/index.php/SunCASA_Installation follow this link] for details regarding the installation of SunCASA on your own machine (only available on Unix-bases OS). This will take you to another page.

EOVSA Data Products

2024-03-29T15:04:03Z

Binchen: /* Level 1.0 - Images and spectrogram data in standard FITS format */

=Introduction=
EOVSA observes the full disk of the Sun at all times when the Sun is >10 degrees above the local horizon (season dependent and ranges from 7-12 hours duration centered on 20 UT). EOVSA records data at 451 science frequency channels each second, in four polarization products, as well as additional total flux measurements from each individual antenna. Raw data in the visibility domain are processed through a pipeline processing system to produce images and spectrograms in the time- and frequency-dependent image plane (the block diagram in Figure 1 shows the data flow in the pipeline).
[[File:pipeline_flowchart.jpg|center|600px|EOVSA pipeline block diagram/flow chart ]]

We deliver the radio interferometry data on the following three levels:

=Level 0 - Raw visibility data from the instrument=

As outlined in Figure 1, EOVSA creates raw data products in the left-hand column (labeled Level 0). This includes observations of cosmic sources for phase calibration, and gain and pointing observations required for total power calibration.

==Raw "Interim" Database (IDB) visibility data==
Full-resolution raw "Interim" Database (IDB) visibility data. They are stored in Miriad format, and hence may not be that useful for most people. Be patient after clicking the link--this is a very long list of directories, one for each available date. These data can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/IDB/

==Raw 1-min-averaged visibility data==
This is the same as for the IDB data, except with 1-minute time integration applied. This is typically not useful for flares, but is perfectly fine for imaging active regions and full Sun. These data can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/UDB/

=Level 0.5 - Calibrated visibility data=
After applying calibration and other preliminary processing to the raw (level 0) data, we create the CASA ms’s in the second column in Figure 1 (labeled "level 0.5"). These visibility data are in the Fourier domain of the true images in the plane of the sky and are not immediately ready for spectral imaging analysis yet. However, they have all of the required content to produce images and spectrogram data in standard FITS format (level 1.0). We provide a set of standard ms’s for each day (red boxes in Figure 1), for use by researchers who know how to deal with visibility data. These data are more suitable for experienced users to exploit the full potential of EOVSA data, such as spatially resolved spectral analysis. Processing these data requires CASA or sunCASA (https://github.com/suncasa/suncasa-src).

==Calibrated full-resolution visibility data for flare events==
Calibrated and self-calibrated visibility data for flare events (purple boxes in Figure 1) will typically be available within 7 days after they are taken. They will be released at our flare list site soon: https://ovsa.njit.edu/flarelist

==Self-calibrated 1-min-averaged visibility data==
EOVSA 1-min averaged visibility data in CASA ms format can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/UDBms_slfcaled

=Level 1.0 - Images and spectrogram data in standard FITS format =

Level 1.0 data are for users who prefer to work with spectrogram (frequency-time) and image data directly, which are also outputs of the pipeline system shown in Figure 1 (orange boxes). They are perfectly suitable to be used as context data for comparison with other multi-wavelength observations but are not (yet) intended for quantitative spatially resolved spectral analysis.

Spectrograms are provided as standard FITS tables containing the frequency list, list of times, and data in both total power (TP) and a sum of amplitudes over intermediate-length baselines (cross power or XP). Likewise, image data products are in FITS format with standard keywords and are converted into the Helioprojective Cartesian coordinate system compatible with the World Coordinate System (WCS) convention, along with correct registration for the spatial, spectral, and temporal coordinates. Both the spectrogram and image data products are calibrated and have physical radio intensity units (sfu for spectrograms and brightness temperature for radio images).

We provide the following data products:
* Synoptic products:
** '''All-day spectrograms''':
** '''All-day synoptic images''':
* Event-based products:
** '''Flare spectrograms''': These are full time and frequency resolution spectrograms produced from the median of calibrated cross-power visibilities in FITS format, cropped to cover the flare duration. Preflare background is also subtracted. Compared to total-power spectrograms, these spectrograms have the advantage of revealing details of the flare evolution by "filtering out" the large-scale, continuous background from the visibilities. Note that for certain flares that have a large source size, the flux can be lower than its true values (as a fraction of the flux will be "resolved out").
** '''Pipeline-produced spectral images''': We also have a semi-automated flare imaging pipeline to produce calibrated (and self-calibrated) images at 12-s cadence at up to 10 frequency bands. They are saved in standard FITS format and have been registered into Helioprojective coordinates. They can be read by SSWIDL or astropy/sunpy. These data have already been calibrated to physical units and are usually good to be compared with context data. But please be cautious when using them for quantitative spectral analysis.

{| class="wikitable"
|+ Summary of EOVSA Level 1 Data Products
|-
! scope="col"| Category
! scope="col"| Data Product
! scope="col"| Naming Convention
! scope="col"| Download Link
|-
! rowspan="2" | Synoptic Spectrograms
| All-day TP Spectrograms
| EOVSA_TPall_yyyymmdd.fts
!rowspan="9" | https://ovsa.njit.edu/browser
|-
| All-day XP Spectrograms
| EOVSA_XPall_yyyymmdd.fts
|-
! rowspan="7" | Synoptic Images
|-
| Synoptic 1.4 GHz images
| eovsa_yyyymmdd.spw00-01.tb.disk.fits
|-
| Synoptic 3.0 GHz images
| eovsa_yyyymmdd.spw02-05.tb.disk.fits
|-
| Synoptic 4.5 GHz images
| eovsa_yyyymmdd.spw06-10.tb.disk.fits
|-
| Synoptic 6.8 GHz images
| eovsa_yyyymmdd.spw11-20.tb.disk.fits
|-
| Synoptic 10.2 GHz images
| eovsa_yyyymmdd.spw21-30.tb.disk.fits
|-
| Synoptic 13.9 GHz images
| eovsa_yyyymmdd.spw31-43.tb.disk.fits
|-
! rowspan="1" | Flare Spectrograms
| Full-resolution cross-power Spectrogram
| eovsa.spec.flare_id_YYYYMMDDHHMMSS.fits
!rowspan="2" | https://ovsa.njit.edu/flarelist
|-
! rowspan="1" | Flare Spectral Images
| Pipeline-produced spectral images
| eovsa.lev1_mbd_12s.YYYY-MM-DDTHHMMSSZ.image.fits
|-
|}

==Browsing and Downloading level 1 data==
[[File:eovsa_browser.jpg|right|thumb|EOVSA Browser]]
[[file:EOVSA_flarelist.jpg|right|thumb|EOVSA Flare List]]
===Synoptic level 1 data===
EOVSA Level 1 synoptic data products can be retrieved with the following steps:
* Go to [http://ovsa.njit.edu/browser/ EOVSA browser] page.
* Browse to the date of interest.
* Click "synoptic fits" button next to the calendar tool.
* Select the data product based on the names listed in the table above.

===Flare level 1 data===
EOVSA flare list with spectrograms and spectral images can be queried and downloaded at https://ovsa.njit.edu/flarelist. Users can use the top box to select a time range of interest and query our flare list. The results are displayed in the dropdown box. An interactive plot of the flare light curves will be shown at the bottom of the page once an event is highlighted (by clicking on the flare ID). Quicklook plots and FITS files of the spectrograms and flare movies can be accessed by clicking the icons in each flare record.

==Reading and Using level 1 data==
===Introduction===
All our level 1 data products are in FITS format. All the images have standard, WCS-compatible coordinates. Users can use their favorite method to read these files. In the following, we provide minimal examples to read them with Astropy and Sunpy.

===Event-Based Data Products===
* An example of how to read and plot the flare spectrograms and images in Python (with Astropy and SunPy) can be accessed at [https://colab.research.google.com/drive/1Y3ONWCxLPYvWda5_LqFNxafJtwZDNJBD?usp=sharing#scrollTo=ueiMoHbdxfo- this Google Colab Jupyter notebook].
* We are working on an example with SSWIDL and will release it soon.

===Synoptic Data Products===

===All-day Spectrograms===
To read a spectrogram file in Python using the suncasa library:

<pre style="background-color: #FCEBD9;">
from suncasa.eovsa import eovsa_dspec as ds
from astropy.time import Time
from matplotlib.colors import LogNorm
## Read EOVSA Dynamic Spectrum FITS file <filename>
filename = 'EOVSA_TPall_20170713.fts'
s = ds.get_dspec(filename, doplot=True, cmap='gist_heat', norm=LogNorm(vmax=2.1e3, vmin=40))
## To access the data in the spectrogram object, use
spec = s['spectrogram'] ## (Array of amplitudes in SFU, of size nfreq,ntimes)
fghz = s['spectrum_axis'] ## (Array of frequencies in GHz, of size nfreq)
tim = Time(s['time_axis'], format='mjd') ## (Array of UT times in astropy.time object, of size ntimes)

</pre>

The '''get_dspec''' function is accessible on [https://github.com/suncasa/suncasa-src/blob/master/suncasa/eovsa/eovsa_dspec.py GitHub]. For comprehensive guidance, please refer to suncasa's [https://suncasa-src.readthedocs.io/en/latest/autoapi/suncasa/eovsa/eovsa_dspec/index.html ReadtheDocs page].
[[File:TPSP.jpeg|center|500px]]

The following code will read the spectrogram file in IDL:

<pre style="background-color: #FCEBD9;">
function dspec,filename,doplot=doplot
; Read EOVSA Dynamic Spectrum FITS file <filename> and return a spectrogram object.
; Optionally show an overview plot if doplot switch is set
;
; Usage:
; s = dspec(<filename>) ; Returns spectrogram object
; s = dspec(<filename>,/doplot) ; Plots spectrum and returns spectrogram object
;
; To access the data in the spectrogram object, use
; spec = s.get(/spectrogram) (Array of amplitudes in SFU, of size ntimes, nfreq)
; fghz = s.get(/spectrum_axis) (Array of frequencies in GHz, of size nfreq)
; ut = s.get(/time_axis) (Array of UT times in anytim format, of size ntimes)

default,doplot,0
spec = mrdfits(filename,0)
freq = mrdfits(filename,1)
time = mrdfits(filename,2)
fghz = freq.sfreq
ut = anytim(time)
s = spectrogram(spec,ut,fghz)
if doplot then begin
window,/free,xsiz=1024,ysiz=600
; Find min and max of data from 5% to 95% of sorted array (eliminates outliers)
sarr = sort(spec)
dlim = minmax(spec[sarr[n_elements(sarr)*0.05:n_elements(sarr)*0.95]])
; Set drange with margin factor of 2 on low end and 5 on high end
s.set,drange=dlim*[0.5,5]
loadct,3
s.plot,/log,/xsty,/ysty,ytitle='Frequency [GHz]',charsize=1.5
endif
return,s
end
</pre>
[[File:IDL_TPSP.png|center|500px]]

===Synoptic 6-band Images===
Full disk images at 6 selected frequency bands centered at 1.4, 3.0, 4.5, 6.8, 10.2, and 13.9 GHz are provided once per day, calibrated in brightness temperature. [[File:synoptic_image.jpg| center |400px]]

The EOVSA full disk image FITS files are compressed with the RICE algorithm implemented in the FITS file handling module (astropy.io.fits) in Astropy. EOVSA FITS files are very similar to the compressed SDO/AIA FITS files from JSOC. Popular coding languages can easily read compressed images directly.

In IDL, you can use read_sdo in the ONTOLOGY package, which should be installed by default in SolarSoftWare (SSW), to read compressed EOVSA FITS files. The following code will read the EOVSA image FITS file in SSWIDL:

<pre style="background-color: #FCEBD9;">
read_sdo,'eovsa_20191225.spw11-20.tb.disk.fits',header,data,/UNCOMP_DELETE
index2map,header,data,eomap
plot_map,eomap
</pre>

[[File:eovsa_20191225_image_sswidl.jpg| center |250px]]

In Python, you can use SunPy map module to read EOVAS FITS files. SunPy is an open solar data analysis environment for Python. The installation instruction can be found at [https://sunpy.org/ SunPy official website].
<pre style="background-color: #FCEBD9;">
import matplotlib.pyplot as plt
from sunpy import map as smap
eofile='eovsa_20191225.spw11-20.tb.disk.fits'
eomap = smap.Map(eofile)
eomap.plot()
plt.show()
</pre>
[[File:eovsa_20191225_image_py.jpg| center |250px]]

We have developed a package for EOVSA data processing and analysis:
[https://github.com/suncasa/suncasa SunCASA] A wrapper around [https://casa.nrao.edu/ CASA (the Common Astronomy Software Applications package)] for synthesis imaging and visualizing solar spectral imaging data. CASA is one of the leading software tools for "supporting the data post-processing needs of the next generation of radio astronomical telescopes such as ALMA and VLA", an international effort led by the [https://public.nrao.edu/ National Radio Astronomy Observatory]. The current version of CASA uses Python (2.7) interface. More information about CASA can be found on [https://casa.nrao.edu/ NRAO's CASA website ]. Note, CASA is available ONLY on UNIX-BASED PLATFORMS (and therefore, so is SunCASA). We are developing a new version of SunCASA based on CASA 6 (which offers a modular approach) so that users have the flexibility to build CASA tools and tasks in their Python environment.

Please [http://www.ovsa.njit.edu/wiki/index.php/SunCASA_Installation follow this link] for details regarding the installation of SunCASA on your own machine (only available on Unix-bases OS). This will take you to another page.

EOVSA Data Products

2024-03-29T15:02:14Z

Binchen: /* Level 1.0 - Images and spectrogram data in standard FITS format */

=Introduction=
EOVSA observes the full disk of the Sun at all times when the Sun is >10 degrees above the local horizon (season dependent and ranges from 7-12 hours duration centered on 20 UT). EOVSA records data at 451 science frequency channels each second, in four polarization products, as well as additional total flux measurements from each individual antenna. Raw data in the visibility domain are processed through a pipeline processing system to produce images and spectrograms in the time- and frequency-dependent image plane (the block diagram in Figure 1 shows the data flow in the pipeline).
[[File:pipeline_flowchart.jpg|center|600px|EOVSA pipeline block diagram/flow chart ]]

We deliver the radio interferometry data on the following three levels:

=Level 0 - Raw visibility data from the instrument=

As outlined in Figure 1, EOVSA creates raw data products in the left-hand column (labeled Level 0). This includes observations of cosmic sources for phase calibration, and gain and pointing observations required for total power calibration.

==Raw "Interim" Database (IDB) visibility data==
Full-resolution raw "Interim" Database (IDB) visibility data. They are stored in Miriad format, and hence may not be that useful for most people. Be patient after clicking the link--this is a very long list of directories, one for each available date. These data can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/IDB/

==Raw 1-min-averaged visibility data==
This is the same as for the IDB data, except with 1-minute time integration applied. This is typically not useful for flares, but is perfectly fine for imaging active regions and full Sun. These data can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/UDB/

=Level 0.5 - Calibrated visibility data=
After applying calibration and other preliminary processing to the raw (level 0) data, we create the CASA ms’s in the second column in Figure 1 (labeled "level 0.5"). These visibility data are in the Fourier domain of the true images in the plane of the sky and are not immediately ready for spectral imaging analysis yet. However, they have all of the required content to produce images and spectrogram data in standard FITS format (level 1.0). We provide a set of standard ms’s for each day (red boxes in Figure 1), for use by researchers who know how to deal with visibility data. These data are more suitable for experienced users to exploit the full potential of EOVSA data, such as spatially resolved spectral analysis. Processing these data requires CASA or sunCASA (https://github.com/suncasa/suncasa-src).

==Calibrated full-resolution visibility data for flare events==
Calibrated and self-calibrated visibility data for flare events (purple boxes in Figure 1) will typically be available within 7 days after they are taken. They will be released at our flare list site soon: https://ovsa.njit.edu/flarelist

==Self-calibrated 1-min-averaged visibility data==
EOVSA 1-min averaged visibility data in CASA ms format can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/UDBms_slfcaled

=Level 1.0 - Images and spectrogram data in standard FITS format =

Level 1.0 data are for users who prefer to work with spectrogram (frequency-time) and image data directly, which are also outputs of the pipeline system shown in Figure 1 (orange boxes). They are perfectly suitable to be used as context data for comparison with other multi-wavelength observations but are not (yet) intended for quantitative spatially resolved spectral analysis.

Spectrograms are provided as standard FITS tables containing the frequency list, list of times, and data in both total power (TP) and a sum of amplitudes over intermediate-length baselines (cross power or XP). Likewise, image data products are in FITS format with standard keywords and are converted into the Helioprojective Cartesian coordinate system compatible with the World Coordinate System (WCS) convention, along with correct registration for the spatial, spectral, and temporal coordinates. Both the spectrogram and image data products are calibrated and have physical radio intensity units (sfu for spectrograms and brightness temperature for radio images).

We provide the following data products:
* Synoptic products:
** '''All-day spectrograms''':
** '''All-day synoptic images''':
* Event-based products:
** '''Flare spectrograms''': These are full time and frequency resolution spectrograms produced from the median of calibrated cross-power visibilities in FITS format, cropped to cover the flare duration. Preflare background is also subtracted. Compared to total-power spectrograms, these spectrograms have the advantage of revealing details of the flare evolution by "filtering out" the large-scale, continuous background from the visibilities. Note that for certain flares that have a large source size, the flux can be lower than its true values (as a fraction of the flux will be "resolved out").
** '''Pipeline-produced spectral images''': We also have a semi-automated flare imaging pipeline to produce calibrated (and self-calibrated) images at 12-s cadence at up to 10 frequency bands. They are saved in standard FITS format and have been registered into Helioprojective coordinates. They can be read by SSWIDL or astropy/sunpy. These data have already been calibrated to physical units and are usually good to be compared with context data. But please be cautious when using them for quantitative spectral analysis.

'''List of Level 1 data products currently provided'''
{| class="wikitable"
|-
! scope="col"| Category
! scope="col"| Data Product
! scope="col"| Naming Convention
! scope="col"| Download Link
|-
! rowspan="2" | Synoptic Spectrograms
| All-day TP Spectrograms
| EOVSA_TPall_yyyymmdd.fts
!rowspan="9" | https://ovsa.njit.edu/browser
|-
| All-day XP Spectrograms
| EOVSA_XPall_yyyymmdd.fts
|-
! rowspan="7" | Synoptic Images
|-
| Synoptic 1.4 GHz images
| eovsa_yyyymmdd.spw00-01.tb.disk.fits
|-
| Synoptic 3.0 GHz images
| eovsa_yyyymmdd.spw02-05.tb.disk.fits
|-
| Synoptic 4.5 GHz images
| eovsa_yyyymmdd.spw06-10.tb.disk.fits
|-
| Synoptic 6.8 GHz images
| eovsa_yyyymmdd.spw11-20.tb.disk.fits
|-
| Synoptic 10.2 GHz images
| eovsa_yyyymmdd.spw21-30.tb.disk.fits
|-
| Synoptic 13.9 GHz images
| eovsa_yyyymmdd.spw31-43.tb.disk.fits
|-
! rowspan="1" | Flare Spectrograms
| Full-resolution cross-power Spectrogram
| eovsa.spec.flare_id_YYYYMMDDHHMMSS.fits
!rowspan="2" | https://ovsa.njit.edu/flarelist
|-
! rowspan="1" | Flare Spectral Images
| Pipeline-produced spectral images
| eovsa.lev1_mbd_12s.YYYY-MM-DDTHHMMSSZ.image.fits
|-
|}

==Browsing and Downloading level 1 data==
[[File:eovsa_browser.jpg|right|thumb|EOVSA Browser]]
[[file:EOVSA_flarelist.jpg|right|thumb|EOVSA Flare List]]
===Synoptic level 1 data===
EOVSA Level 1 synoptic data products can be retrieved with the following steps:
* Go to [http://ovsa.njit.edu/browser/ EOVSA browser] page.
* Browse to the date of interest.
* Click "synoptic fits" button next to the calendar tool.
* Select the data product based on the names listed in the table above.

===Flare level 1 data===
EOVSA flare list with spectrograms and spectral images can be queried and downloaded at https://ovsa.njit.edu/flarelist. Users can use the top box to select a time range of interest and query our flare list. The results are displayed in the dropdown box. An interactive plot of the flare light curves will be shown at the bottom of the page once an event is highlighted (by clicking on the flare ID). Quicklook plots and FITS files of the spectrograms and flare movies can be accessed by clicking the icons in each flare record.

==Reading and Using level 1 data==
===Introduction===
All our level 1 data products are in FITS format. All the images have standard, WCS-compatible coordinates. Users can use their favorite method to read these files. In the following, we provide minimal examples to read them with Astropy and Sunpy.

===Event-Based Data Products===
* An example of how to read and plot the flare spectrograms and images in Python (with Astropy and SunPy) can be accessed at [https://colab.research.google.com/drive/1Y3ONWCxLPYvWda5_LqFNxafJtwZDNJBD?usp=sharing#scrollTo=ueiMoHbdxfo- this Google Colab Jupyter notebook].
* We are working on an example with SSWIDL and will release it soon.

===Synoptic Data Products===

===All-day Spectrograms===
To read a spectrogram file in Python using the suncasa library:

<pre style="background-color: #FCEBD9;">
from suncasa.eovsa import eovsa_dspec as ds
from astropy.time import Time
from matplotlib.colors import LogNorm
## Read EOVSA Dynamic Spectrum FITS file <filename>
filename = 'EOVSA_TPall_20170713.fts'
s = ds.get_dspec(filename, doplot=True, cmap='gist_heat', norm=LogNorm(vmax=2.1e3, vmin=40))
## To access the data in the spectrogram object, use
spec = s['spectrogram'] ## (Array of amplitudes in SFU, of size nfreq,ntimes)
fghz = s['spectrum_axis'] ## (Array of frequencies in GHz, of size nfreq)
tim = Time(s['time_axis'], format='mjd') ## (Array of UT times in astropy.time object, of size ntimes)

</pre>

The '''get_dspec''' function is accessible on [https://github.com/suncasa/suncasa-src/blob/master/suncasa/eovsa/eovsa_dspec.py GitHub]. For comprehensive guidance, please refer to suncasa's [https://suncasa-src.readthedocs.io/en/latest/autoapi/suncasa/eovsa/eovsa_dspec/index.html ReadtheDocs page].
[[File:TPSP.jpeg|center|500px]]

The following code will read the spectrogram file in IDL:

<pre style="background-color: #FCEBD9;">
function dspec,filename,doplot=doplot
; Read EOVSA Dynamic Spectrum FITS file <filename> and return a spectrogram object.
; Optionally show an overview plot if doplot switch is set
;
; Usage:
; s = dspec(<filename>) ; Returns spectrogram object
; s = dspec(<filename>,/doplot) ; Plots spectrum and returns spectrogram object
;
; To access the data in the spectrogram object, use
; spec = s.get(/spectrogram) (Array of amplitudes in SFU, of size ntimes, nfreq)
; fghz = s.get(/spectrum_axis) (Array of frequencies in GHz, of size nfreq)
; ut = s.get(/time_axis) (Array of UT times in anytim format, of size ntimes)

default,doplot,0
spec = mrdfits(filename,0)
freq = mrdfits(filename,1)
time = mrdfits(filename,2)
fghz = freq.sfreq
ut = anytim(time)
s = spectrogram(spec,ut,fghz)
if doplot then begin
window,/free,xsiz=1024,ysiz=600
; Find min and max of data from 5% to 95% of sorted array (eliminates outliers)
sarr = sort(spec)
dlim = minmax(spec[sarr[n_elements(sarr)*0.05:n_elements(sarr)*0.95]])
; Set drange with margin factor of 2 on low end and 5 on high end
s.set,drange=dlim*[0.5,5]
loadct,3
s.plot,/log,/xsty,/ysty,ytitle='Frequency [GHz]',charsize=1.5
endif
return,s
end
</pre>
[[File:IDL_TPSP.png|center|500px]]

===Synoptic 6-band Images===
Full disk images at 6 selected frequency bands centered at 1.4, 3.0, 4.5, 6.8, 10.2, and 13.9 GHz are provided once per day, calibrated in brightness temperature. [[File:synoptic_image.jpg| center |400px]]

The EOVSA full disk image FITS files are compressed with the RICE algorithm implemented in the FITS file handling module (astropy.io.fits) in Astropy. EOVSA FITS files are very similar to the compressed SDO/AIA FITS files from JSOC. Popular coding languages can easily read compressed images directly.

In IDL, you can use read_sdo in the ONTOLOGY package, which should be installed by default in SolarSoftWare (SSW), to read compressed EOVSA FITS files. The following code will read the EOVSA image FITS file in SSWIDL:

<pre style="background-color: #FCEBD9;">
read_sdo,'eovsa_20191225.spw11-20.tb.disk.fits',header,data,/UNCOMP_DELETE
index2map,header,data,eomap
plot_map,eomap
</pre>

[[File:eovsa_20191225_image_sswidl.jpg| center |250px]]

In Python, you can use SunPy map module to read EOVAS FITS files. SunPy is an open solar data analysis environment for Python. The installation instruction can be found at [https://sunpy.org/ SunPy official website].
<pre style="background-color: #FCEBD9;">
import matplotlib.pyplot as plt
from sunpy import map as smap
eofile='eovsa_20191225.spw11-20.tb.disk.fits'
eomap = smap.Map(eofile)
eomap.plot()
plt.show()
</pre>
[[File:eovsa_20191225_image_py.jpg| center |250px]]

We have developed a package for EOVSA data processing and analysis:
[https://github.com/suncasa/suncasa SunCASA] A wrapper around [https://casa.nrao.edu/ CASA (the Common Astronomy Software Applications package)] for synthesis imaging and visualizing solar spectral imaging data. CASA is one of the leading software tools for "supporting the data post-processing needs of the next generation of radio astronomical telescopes such as ALMA and VLA", an international effort led by the [https://public.nrao.edu/ National Radio Astronomy Observatory]. The current version of CASA uses Python (2.7) interface. More information about CASA can be found on [https://casa.nrao.edu/ NRAO's CASA website ]. Note, CASA is available ONLY on UNIX-BASED PLATFORMS (and therefore, so is SunCASA). We are developing a new version of SunCASA based on CASA 6 (which offers a modular approach) so that users have the flexibility to build CASA tools and tasks in their Python environment.

Please [http://www.ovsa.njit.edu/wiki/index.php/SunCASA_Installation follow this link] for details regarding the installation of SunCASA on your own machine (only available on Unix-bases OS). This will take you to another page.

EOVSA Data Products

2024-03-29T14:54:43Z

Binchen: /* Reading level 1 data */

=Introduction=
EOVSA observes the full disk of the Sun at all times when the Sun is >10 degrees above the local horizon (season dependent and ranges from 7-12 hours duration centered on 20 UT). EOVSA records data at 451 science frequency channels each second, in four polarization products, as well as additional total flux measurements from each individual antenna. Raw data in the visibility domain are processed through a pipeline processing system to produce images and spectrograms in the time- and frequency-dependent image plane (the block diagram in Figure 1 shows the data flow in the pipeline).
[[File:pipeline_flowchart.jpg|center|600px|EOVSA pipeline block diagram/flow chart ]]

We deliver the radio interferometry data on the following three levels:

=Level 0 - Raw visibility data from the instrument=

As outlined in Figure 1, EOVSA creates raw data products in the left-hand column (labeled Level 0). This includes observations of cosmic sources for phase calibration, and gain and pointing observations required for total power calibration.

==Raw "Interim" Database (IDB) visibility data==
Full-resolution raw "Interim" Database (IDB) visibility data. They are stored in Miriad format, and hence may not be that useful for most people. Be patient after clicking the link--this is a very long list of directories, one for each available date. These data can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/IDB/

==Raw 1-min-averaged visibility data==
This is the same as for the IDB data, except with 1-minute time integration applied. This is typically not useful for flares, but is perfectly fine for imaging active regions and full Sun. These data can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/UDB/

=Level 0.5 - Calibrated visibility data=
After applying calibration and other preliminary processing to the raw (level 0) data, we create the CASA ms’s in the second column in Figure 1 (labeled "level 0.5"). These visibility data are in the Fourier domain of the true images in the plane of the sky and are not immediately ready for spectral imaging analysis yet. However, they have all of the required content to produce images and spectrogram data in standard FITS format (level 1.0). We provide a set of standard ms’s for each day (red boxes in Figure 1), for use by researchers who know how to deal with visibility data. These data are more suitable for experienced users to exploit the full potential of EOVSA data, such as spatially resolved spectral analysis. Processing these data requires CASA or sunCASA (https://github.com/suncasa/suncasa-src).

==Calibrated full-resolution visibility data for flare events==
Calibrated and self-calibrated visibility data for flare events (purple boxes in Figure 1) will typically be available within 7 days after they are taken. They will be released at our flare list site soon: https://ovsa.njit.edu/flarelist

==Self-calibrated 1-min-averaged visibility data==
EOVSA 1-min averaged visibility data in CASA ms format can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/UDBms_slfcaled

=Level 1.0 - Images and spectrogram data in standard FITS format =

Level 1.0 data are for users who prefer to work with spectrogram (frequency-time) and image data directly, which are also outputs of the pipeline system shown in Figure 1 (orange boxes). They are perfectly suitable to be used as context data for comparison with other multi-wavelength observations but are not (yet) intended for quantitative spatially resolved spectral analysis.

Spectrograms are provided as standard FITS tables containing the frequency list, list of times, and data in both total power (TP) and a sum of amplitudes over intermediate-length baselines (cross power or XP). Likewise, image data products are in FITS format with standard keywords and are converted into the Helioprojective Cartesian coordinate system compatible with the World Coordinate System (WCS) convention, along with correct registration for the spatial, spectral, and temporal coordinates. Both the spectrogram and image data products are calibrated and have physical radio intensity units (sfu for spectrograms and brightness temperature for radio images).

We provide the following data products:
* Synoptic products:
** '''All-day total-power spectrograms''':
** '''All-day cross-power spectrograms''':
** '''All-day synoptic images''':
* Event-based products:
** '''Flare spectrograms''': These are full time and frequency resolution spectrograms produced from the median of calibrated cross-power visibilities in FITS format, cropped to cover the flare duration. Preflare background is also subtracted. Compared to total-power spectrograms, these spectrograms have the advantage of revealing details of the flare evolution by "filtering out" the large-scale, continuous background from the visibilities. Note that for certain flares that have a large source size, the flux can be lower than its true values (as a fraction of the flux will be "resolved out").
** '''Pipeline-produced spectral images''': We also have a semi-automated flare imaging pipeline to produce calibrated (and self-calibrated) images at 12-s cadence at up to 10 frequency bands. They are saved in standard FITS format and have been registered into Helioprojective coordinates. They can be read by SSWIDL or astropy/sunpy. These data have already been calibrated to physical units and are usually good to be compared with context data. But please be cautious when using them for quantitative spectral analysis.

'''List of Level 1 data products currently provided'''
{| class="wikitable"
|-
! scope="col"| Category
! scope="col"| Data Product
! scope="col"| Naming Convention
! scope="col"| Download Link
|-
! rowspan="2" | Synoptic Spectrograms
| All-day TP Spectrograms
| EOVSA_TPall_yyyymmdd.fts
!rowspan="9" | https://ovsa.njit.edu/browser
|-
| All-day XP Spectrograms
| EOVSA_XPall_yyyymmdd.fts
|-
! rowspan="7" | Synoptic Images
|-
| Synoptic 1.4 GHz images
| eovsa_yyyymmdd.spw00-01.tb.disk.fits
|-
| Synoptic 3.0 GHz images
| eovsa_yyyymmdd.spw02-05.tb.disk.fits
|-
| Synoptic 4.5 GHz images
| eovsa_yyyymmdd.spw06-10.tb.disk.fits
|-
| Synoptic 6.8 GHz images
| eovsa_yyyymmdd.spw11-20.tb.disk.fits
|-
| Synoptic 10.2 GHz images
| eovsa_yyyymmdd.spw21-30.tb.disk.fits
|-
| Synoptic 13.9 GHz images
| eovsa_yyyymmdd.spw31-43.tb.disk.fits
|-
! rowspan="1" | Flare Spectrograms
| Full-resolution cross-power Spectrogram
| eovsa.spec.flare_id_YYYYMMDDHHMMSS.fits
!rowspan="2" | https://ovsa.njit.edu/flarelist
|-
! rowspan="1" | Flare Spectral Images
| Pipeline-produced spectral images
| eovsa.lev1_mbd_12s.YYYY-MM-DDTHHMMSSZ.image.fits
|-
|}

==Browsing and Downloading level 1 data==
[[File:eovsa_browser.jpg|right|thumb|EOVSA Browser]]
[[file:EOVSA_flarelist.jpg|right|thumb|EOVSA Flare List]]
===Synoptic level 1 data===
EOVSA Level 1 synoptic data products can be retrieved with the following steps:
* Go to [http://ovsa.njit.edu/browser/ EOVSA browser] page.
* Browse to the date of interest.
* Click "synoptic fits" button next to the calendar tool.
* Select the data product based on the names listed in the table above.

===Flare level 1 data===
EOVSA flare list with spectrograms and spectral images can be queried and downloaded at https://ovsa.njit.edu/flarelist. Users can use the top box to select a time range of interest and query our flare list. The results are displayed in the dropdown box. An interactive plot of the flare light curves will be shown at the bottom of the page once an event is highlighted (by clicking on the flare ID). Quicklook plots and FITS files of the spectrograms and flare movies can be accessed by clicking the icons in each flare record.

==Reading and Using level 1 data==
===Introduction===
All our level 1 data products are in FITS format. All the images have standard, WCS-compatible coordinates. Users can use their favorite method to read these files. In the following, we provide minimal examples to read them with Astropy and Sunpy.

===Event-Based Data Products===
* An example of how to read and plot the flare spectrograms and images in Python (with Astropy and SunPy) can be accessed at [https://colab.research.google.com/drive/1Y3ONWCxLPYvWda5_LqFNxafJtwZDNJBD?usp=sharing#scrollTo=ueiMoHbdxfo- this Google Colab Jupyter notebook].
* We are working on an example with SSWIDL and will release it soon.

===Synoptic Data Products===

===All-day Spectrograms===
To read a spectrogram file in Python using the suncasa library:

<pre style="background-color: #FCEBD9;">
from suncasa.eovsa import eovsa_dspec as ds
from astropy.time import Time
from matplotlib.colors import LogNorm
## Read EOVSA Dynamic Spectrum FITS file <filename>
filename = 'EOVSA_TPall_20170713.fts'
s = ds.get_dspec(filename, doplot=True, cmap='gist_heat', norm=LogNorm(vmax=2.1e3, vmin=40))
## To access the data in the spectrogram object, use
spec = s['spectrogram'] ## (Array of amplitudes in SFU, of size nfreq,ntimes)
fghz = s['spectrum_axis'] ## (Array of frequencies in GHz, of size nfreq)
tim = Time(s['time_axis'], format='mjd') ## (Array of UT times in astropy.time object, of size ntimes)

</pre>

The '''get_dspec''' function is accessible on [https://github.com/suncasa/suncasa-src/blob/master/suncasa/eovsa/eovsa_dspec.py GitHub]. For comprehensive guidance, please refer to suncasa's [https://suncasa-src.readthedocs.io/en/latest/autoapi/suncasa/eovsa/eovsa_dspec/index.html ReadtheDocs page].
[[File:TPSP.jpeg|center|500px]]

The following code will read the spectrogram file in IDL:

<pre style="background-color: #FCEBD9;">
function dspec,filename,doplot=doplot
; Read EOVSA Dynamic Spectrum FITS file <filename> and return a spectrogram object.
; Optionally show an overview plot if doplot switch is set
;
; Usage:
; s = dspec(<filename>) ; Returns spectrogram object
; s = dspec(<filename>,/doplot) ; Plots spectrum and returns spectrogram object
;
; To access the data in the spectrogram object, use
; spec = s.get(/spectrogram) (Array of amplitudes in SFU, of size ntimes, nfreq)
; fghz = s.get(/spectrum_axis) (Array of frequencies in GHz, of size nfreq)
; ut = s.get(/time_axis) (Array of UT times in anytim format, of size ntimes)

default,doplot,0
spec = mrdfits(filename,0)
freq = mrdfits(filename,1)
time = mrdfits(filename,2)
fghz = freq.sfreq
ut = anytim(time)
s = spectrogram(spec,ut,fghz)
if doplot then begin
window,/free,xsiz=1024,ysiz=600
; Find min and max of data from 5% to 95% of sorted array (eliminates outliers)
sarr = sort(spec)
dlim = minmax(spec[sarr[n_elements(sarr)*0.05:n_elements(sarr)*0.95]])
; Set drange with margin factor of 2 on low end and 5 on high end
s.set,drange=dlim*[0.5,5]
loadct,3
s.plot,/log,/xsty,/ysty,ytitle='Frequency [GHz]',charsize=1.5
endif
return,s
end
</pre>
[[File:IDL_TPSP.png|center|500px]]

===Synoptic 6-band Images===
Full disk images at 6 selected frequency bands centered at 1.4, 3.0, 4.5, 6.8, 10.2, and 13.9 GHz are provided once per day, calibrated in brightness temperature. [[File:synoptic_image.jpg| center |400px]]

The EOVSA full disk image FITS files are compressed with the RICE algorithm implemented in the FITS file handling module (astropy.io.fits) in Astropy. EOVSA FITS files are very similar to the compressed SDO/AIA FITS files from JSOC. Popular coding languages can easily read compressed images directly.

In IDL, you can use read_sdo in the ONTOLOGY package, which should be installed by default in SolarSoftWare (SSW), to read compressed EOVSA FITS files. The following code will read the EOVSA image FITS file in SSWIDL:

<pre style="background-color: #FCEBD9;">
read_sdo,'eovsa_20191225.spw11-20.tb.disk.fits',header,data,/UNCOMP_DELETE
index2map,header,data,eomap
plot_map,eomap
</pre>

[[File:eovsa_20191225_image_sswidl.jpg| center |250px]]

In Python, you can use SunPy map module to read EOVAS FITS files. SunPy is an open solar data analysis environment for Python. The installation instruction can be found at [https://sunpy.org/ SunPy official website].
<pre style="background-color: #FCEBD9;">
import matplotlib.pyplot as plt
from sunpy import map as smap
eofile='eovsa_20191225.spw11-20.tb.disk.fits'
eomap = smap.Map(eofile)
eomap.plot()
plt.show()
</pre>
[[File:eovsa_20191225_image_py.jpg| center |250px]]

We have developed a package for EOVSA data processing and analysis:
[https://github.com/suncasa/suncasa SunCASA] A wrapper around [https://casa.nrao.edu/ CASA (the Common Astronomy Software Applications package)] for synthesis imaging and visualizing solar spectral imaging data. CASA is one of the leading software tools for "supporting the data post-processing needs of the next generation of radio astronomical telescopes such as ALMA and VLA", an international effort led by the [https://public.nrao.edu/ National Radio Astronomy Observatory]. The current version of CASA uses Python (2.7) interface. More information about CASA can be found on [https://casa.nrao.edu/ NRAO's CASA website ]. Note, CASA is available ONLY on UNIX-BASED PLATFORMS (and therefore, so is SunCASA). We are developing a new version of SunCASA based on CASA 6 (which offers a modular approach) so that users have the flexibility to build CASA tools and tasks in their Python environment.

Please [http://www.ovsa.njit.edu/wiki/index.php/SunCASA_Installation follow this link] for details regarding the installation of SunCASA on your own machine (only available on Unix-bases OS). This will take you to another page.

EOVSA Data Products

2024-03-29T14:42:02Z

Binchen: /* Level 1.0 - Images and spectrogram data in standard FITS format */

=Introduction=
EOVSA observes the full disk of the Sun at all times when the Sun is >10 degrees above the local horizon (season dependent and ranges from 7-12 hours duration centered on 20 UT). EOVSA records data at 451 science frequency channels each second, in four polarization products, as well as additional total flux measurements from each individual antenna. Raw data in the visibility domain are processed through a pipeline processing system to produce images and spectrograms in the time- and frequency-dependent image plane (the block diagram in Figure 1 shows the data flow in the pipeline).
[[File:pipeline_flowchart.jpg|center|600px|EOVSA pipeline block diagram/flow chart ]]

We deliver the radio interferometry data on the following three levels:

=Level 0 - Raw visibility data from the instrument=

As outlined in Figure 1, EOVSA creates raw data products in the left-hand column (labeled Level 0). This includes observations of cosmic sources for phase calibration, and gain and pointing observations required for total power calibration.

==Raw "Interim" Database (IDB) visibility data==
Full-resolution raw "Interim" Database (IDB) visibility data. They are stored in Miriad format, and hence may not be that useful for most people. Be patient after clicking the link--this is a very long list of directories, one for each available date. These data can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/IDB/

==Raw 1-min-averaged visibility data==
This is the same as for the IDB data, except with 1-minute time integration applied. This is typically not useful for flares, but is perfectly fine for imaging active regions and full Sun. These data can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/UDB/

=Level 0.5 - Calibrated visibility data=
After applying calibration and other preliminary processing to the raw (level 0) data, we create the CASA ms’s in the second column in Figure 1 (labeled "level 0.5"). These visibility data are in the Fourier domain of the true images in the plane of the sky and are not immediately ready for spectral imaging analysis yet. However, they have all of the required content to produce images and spectrogram data in standard FITS format (level 1.0). We provide a set of standard ms’s for each day (red boxes in Figure 1), for use by researchers who know how to deal with visibility data. These data are more suitable for experienced users to exploit the full potential of EOVSA data, such as spatially resolved spectral analysis. Processing these data requires CASA or sunCASA (https://github.com/suncasa/suncasa-src).

==Calibrated full-resolution visibility data for flare events==
Calibrated and self-calibrated visibility data for flare events (purple boxes in Figure 1) will typically be available within 7 days after they are taken. They will be released at our flare list site soon: https://ovsa.njit.edu/flarelist

==Self-calibrated 1-min-averaged visibility data==
EOVSA 1-min averaged visibility data in CASA ms format can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/UDBms_slfcaled

=Level 1.0 - Images and spectrogram data in standard FITS format =

Level 1.0 data are for users who prefer to work with spectrogram (frequency-time) and image data directly, which are also outputs of the pipeline system shown in Figure 1 (orange boxes). They are perfectly suitable to be used as context data for comparison with other multi-wavelength observations but are not (yet) intended for quantitative spatially resolved spectral analysis.

Spectrograms are provided as standard FITS tables containing the frequency list, list of times, and data in both total power (TP) and a sum of amplitudes over intermediate-length baselines (cross power or XP). Likewise, image data products are in FITS format with standard keywords and are converted into the Helioprojective Cartesian coordinate system compatible with the World Coordinate System (WCS) convention, along with correct registration for the spatial, spectral, and temporal coordinates. Both the spectrogram and image data products are calibrated and have physical radio intensity units (sfu for spectrograms and brightness temperature for radio images).

We provide the following data products:
* Synoptic products:
** '''All-day total-power spectrograms''':
** '''All-day cross-power spectrograms''':
** '''All-day synoptic images''':
* Event-based products:
** '''Flare spectrograms''': These are full time and frequency resolution spectrograms produced from the median of calibrated cross-power visibilities in FITS format, cropped to cover the flare duration. Preflare background is also subtracted. Compared to total-power spectrograms, these spectrograms have the advantage of revealing details of the flare evolution by "filtering out" the large-scale, continuous background from the visibilities. Note that for certain flares that have a large source size, the flux can be lower than its true values (as a fraction of the flux will be "resolved out").
** '''Pipeline-produced spectral images''': We also have a semi-automated flare imaging pipeline to produce calibrated (and self-calibrated) images at 12-s cadence at up to 10 frequency bands. They are saved in standard FITS format and have been registered into Helioprojective coordinates. They can be read by SSWIDL or astropy/sunpy. These data have already been calibrated to physical units and are usually good to be compared with context data. But please be cautious when using them for quantitative spectral analysis.

'''List of Level 1 data products currently provided'''
{| class="wikitable"
|-
! scope="col"| Category
! scope="col"| Data Product
! scope="col"| Naming Convention
! scope="col"| Download Link
|-
! rowspan="2" | Synoptic Spectrograms
| All-day TP Spectrograms
| EOVSA_TPall_yyyymmdd.fts
!rowspan="9" | https://ovsa.njit.edu/browser
|-
| All-day XP Spectrograms
| EOVSA_XPall_yyyymmdd.fts
|-
! rowspan="7" | Synoptic Images
|-
| Synoptic 1.4 GHz images
| eovsa_yyyymmdd.spw00-01.tb.disk.fits
|-
| Synoptic 3.0 GHz images
| eovsa_yyyymmdd.spw02-05.tb.disk.fits
|-
| Synoptic 4.5 GHz images
| eovsa_yyyymmdd.spw06-10.tb.disk.fits
|-
| Synoptic 6.8 GHz images
| eovsa_yyyymmdd.spw11-20.tb.disk.fits
|-
| Synoptic 10.2 GHz images
| eovsa_yyyymmdd.spw21-30.tb.disk.fits
|-
| Synoptic 13.9 GHz images
| eovsa_yyyymmdd.spw31-43.tb.disk.fits
|-
! rowspan="1" | Flare Spectrograms
| Full-resolution cross-power Spectrogram
| eovsa.spec.flare_id_YYYYMMDDHHMMSS.fits
!rowspan="2" | https://ovsa.njit.edu/flarelist
|-
! rowspan="1" | Flare Spectral Images
| Pipeline-produced spectral images
| eovsa.lev1_mbd_12s.YYYY-MM-DDTHHMMSSZ.image.fits
|-
|}

==Browsing and Downloading level 1 data==
[[File:eovsa_browser.jpg|right|thumb|EOVSA Browser]]
[[file:EOVSA_flarelist.jpg|right|thumb|EOVSA Flare List]]
===Synoptic level 1 data===
EOVSA Level 1 synoptic data products can be retrieved with the following steps:
* Go to [http://ovsa.njit.edu/browser/ EOVSA browser] page.
* Browse to the date of interest.
* Click "synoptic fits" button next to the calendar tool.
* Select the data product based on the names listed in the table above.

===Flare level 1 data===
EOVSA flare list with spectrograms and spectral images can be queried and downloaded at https://ovsa.njit.edu/flarelist. Users can use the top box to select a time range of interest and query our flare list. The results are displayed in the dropdown box. An interactive plot of the flare light curves will be shown at the bottom of the page once an event is highlighted (by clicking on the flare ID). Quicklook plots and FITS files of the spectrograms and flare movies can be accessed by clicking the icons in each flare record.

==Reading level 1 data==
===Software===
We have developed a package for EOVSA data processing and analysis:
[https://github.com/suncasa/suncasa SunCASA] A wrapper around [https://casa.nrao.edu/ CASA (the Common Astronomy Software Applications package)] for synthesis imaging and visualizing solar spectral imaging data. CASA is one of the leading software tools for "supporting the data post-processing needs of the next generation of radio astronomical telescopes such as ALMA and VLA", an international effort led by the [https://public.nrao.edu/ National Radio Astronomy Observatory]. The current version of CASA uses Python (2.7) interface. More information about CASA can be found on [https://casa.nrao.edu/ NRAO's CASA website ]. Note, CASA is available ONLY on UNIX-BASED PLATFORMS (and therefore, so is SunCASA). We are developing a new version of SunCASA based on CASA 6 (which offers a modular approach) so that users have the flexibility to build CASA tools and tasks in their Python environment.

Please [http://www.ovsa.njit.edu/wiki/index.php/SunCASA_Installation follow this link] for details regarding the installation of SunCASA on your own machine (only available on Unix-bases OS). This will take you to another page.

===Flare Spectrograms and Multi-Frequency Images ===
* An example of how to read and plot these FITS data in Python (with Astropy and SunPy) can be accessed at [https://colab.research.google.com/drive/1Y3ONWCxLPYvWda5_LqFNxafJtwZDNJBD?usp=sharing#scrollTo=ueiMoHbdxfo- this Google Colab Jupyter notebook].
* We are working on an example with SSWIDL and will release it soon.

===All-day TP spectrum===
Daily total power full-Sun-integrated spectrogram calibrated in solar flux units are provided at 451 frequencies (134 frequencies prior to 2019 Feb 22) and 1 s time resolution.

To read a spectrogram file in Python using the suncasa library:

<pre style="background-color: #FCEBD9;">
from suncasa.eovsa import eovsa_dspec as ds
from astropy.time import Time
from matplotlib.colors import LogNorm
## Read EOVSA Dynamic Spectrum FITS file <filename>
filename = 'EOVSA_TPall_20170713.fts'
s = ds.get_dspec(filename, doplot=True, cmap='gist_heat', norm=LogNorm(vmax=2.1e3, vmin=40))
## To access the data in the spectrogram object, use
spec = s['spectrogram'] ## (Array of amplitudes in SFU, of size nfreq,ntimes)
fghz = s['spectrum_axis'] ## (Array of frequencies in GHz, of size nfreq)
tim = Time(s['time_axis'], format='mjd') ## (Array of UT times in astropy.time object, of size ntimes)

</pre>

The '''get_dspec''' function is accessible on [https://github.com/suncasa/suncasa-src/blob/master/suncasa/eovsa/eovsa_dspec.py GitHub]. For comprehensive guidance, please refer to suncasa's [https://suncasa-src.readthedocs.io/en/latest/autoapi/suncasa/eovsa/eovsa_dspec/index.html ReadtheDocs page].
[[File:TPSP.jpeg|center|500px]]

The following code will read the spectrogram file in IDL:

<pre style="background-color: #FCEBD9;">
function dspec,filename,doplot=doplot
; Read EOVSA Dynamic Spectrum FITS file <filename> and return a spectrogram object.
; Optionally show an overview plot if doplot switch is set
;
; Usage:
; s = dspec(<filename>) ; Returns spectrogram object
; s = dspec(<filename>,/doplot) ; Plots spectrum and returns spectrogram object
;
; To access the data in the spectrogram object, use
; spec = s.get(/spectrogram) (Array of amplitudes in SFU, of size ntimes, nfreq)
; fghz = s.get(/spectrum_axis) (Array of frequencies in GHz, of size nfreq)
; ut = s.get(/time_axis) (Array of UT times in anytim format, of size ntimes)

default,doplot,0
spec = mrdfits(filename,0)
freq = mrdfits(filename,1)
time = mrdfits(filename,2)
fghz = freq.sfreq
ut = anytim(time)
s = spectrogram(spec,ut,fghz)
if doplot then begin
window,/free,xsiz=1024,ysiz=600
; Find min and max of data from 5% to 95% of sorted array (eliminates outliers)
sarr = sort(spec)
dlim = minmax(spec[sarr[n_elements(sarr)*0.05:n_elements(sarr)*0.95]])
; Set drange with margin factor of 2 on low end and 5 on high end
s.set,drange=dlim*[0.5,5]
loadct,3
s.plot,/log,/xsty,/ysty,ytitle='Frequency [GHz]',charsize=1.5
endif
return,s
end
</pre>
[[File:IDL_TPSP.png|center|500px]]

===Synoptic 6-band Images===
Full disk images at 6 selected frequency bands centered at 1.4, 3.0, 4.5, 6.8, 10.2, and 13.9 GHz are provided once per day, calibrated in brightness temperature. [[File:synoptic_image.jpg| center |400px]]

The EOVSA full disk image FITS files are compressed with the RICE algorithm implemented in the FITS file handling module (astropy.io.fits) in Astropy. EOVSA FITS files are very similar to the compressed SDO/AIA FITS files from JSOC. Popular coding languages can easily read compressed images directly.

In IDL, you can use read_sdo in the ONTOLOGY package, which should be installed by default in SolarSoftWare (SSW), to read compressed EOVSA FITS files. The following code will read the EOVSA image FITS file in SSWIDL:

<pre style="background-color: #FCEBD9;">
read_sdo,'eovsa_20191225.spw11-20.tb.disk.fits',header,data,/UNCOMP_DELETE
index2map,header,data,eomap
plot_map,eomap
</pre>

[[File:eovsa_20191225_image_sswidl.jpg| center |250px]]

In Python, you can use SunPy map module to read EOVAS FITS files. SunPy is an open solar data analysis environment for Python. The installation instruction can be found at [https://sunpy.org/ SunPy official website].
<pre style="background-color: #FCEBD9;">
import matplotlib.pyplot as plt
from sunpy import map as smap
eofile='eovsa_20191225.spw11-20.tb.disk.fits'
eomap = smap.Map(eofile)
eomap.plot()
plt.show()
</pre>
[[File:eovsa_20191225_image_py.jpg| center |250px]]

Although the Sunpy Python package already exists for doing analysis of solar data, it has a significant learning curve and lacks the generality of the Mapping routines written by Dominic Zarro for the IDL-based Solarsoft (SSW). We provided IDL Mapping routines available in Python that may help those IDL users who have been avoiding learning Python. '''The mapping routines work equally well in both Python 2.7 and Python 3'''.
Get the [http://www.ovsa.njit.edu/wiki/index.php/Mapping_Software Mapping routines]
The following code will read the EOVSA image FITS file in python:
<pre style="background-color: #FCEBD9;">
from mapping.plot_map import plot_map
from mapping.fits2map import fits2map
eofile='eovsa_20191225.spw11-20.tb.disk.fits'
eomap, h = fits2map(eofile,header=True)
plot_map(eomap, grid=15, limb=True,cmap='gray')
</pre>
[[File:eovsa_20191225_image_py_ssw-mapping.jpg| center |250px]]

EOVSA Data Products

2024-03-29T14:36:20Z

Binchen: /* Level 0.5 - Calibrated visibility data */

=Introduction=
EOVSA observes the full disk of the Sun at all times when the Sun is >10 degrees above the local horizon (season dependent and ranges from 7-12 hours duration centered on 20 UT). EOVSA records data at 451 science frequency channels each second, in four polarization products, as well as additional total flux measurements from each individual antenna. Raw data in the visibility domain are processed through a pipeline processing system to produce images and spectrograms in the time- and frequency-dependent image plane (the block diagram in Figure 1 shows the data flow in the pipeline).
[[File:pipeline_flowchart.jpg|center|600px|EOVSA pipeline block diagram/flow chart ]]

We deliver the radio interferometry data on the following three levels:

=Level 0 - Raw visibility data from the instrument=

As outlined in Figure 1, EOVSA creates raw data products in the left-hand column (labeled Level 0). This includes observations of cosmic sources for phase calibration, and gain and pointing observations required for total power calibration.

==Raw "Interim" Database (IDB) visibility data==
Full-resolution raw "Interim" Database (IDB) visibility data. They are stored in Miriad format, and hence may not be that useful for most people. Be patient after clicking the link--this is a very long list of directories, one for each available date. These data can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/IDB/

==Raw 1-min-averaged visibility data==
This is the same as for the IDB data, except with 1-minute time integration applied. This is typically not useful for flares, but is perfectly fine for imaging active regions and full Sun. These data can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/UDB/

=Level 0.5 - Calibrated visibility data=
After applying calibration and other preliminary processing to the raw (level 0) data, we create the CASA ms’s in the second column in Figure 1 (labeled "level 0.5"). These visibility data are in the Fourier domain of the true images in the plane of the sky and are not immediately ready for spectral imaging analysis yet. However, they have all of the required content to produce images and spectrogram data in standard FITS format (level 1.0). We provide a set of standard ms’s for each day (red boxes in Figure 1), for use by researchers who know how to deal with visibility data. These data are more suitable for experienced users to exploit the full potential of EOVSA data, such as spatially resolved spectral analysis. Processing these data requires CASA or sunCASA (https://github.com/suncasa/suncasa-src).

==Calibrated full-resolution visibility data for flare events==
Calibrated and self-calibrated visibility data for flare events (purple boxes in Figure 1) will typically be available within 7 days after they are taken. They will be released at our flare list site soon: https://ovsa.njit.edu/flarelist

==Self-calibrated 1-min-averaged visibility data==
EOVSA 1-min averaged visibility data in CASA ms format can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/UDBms_slfcaled

=Level 1.0 - Images and spectrogram data in standard FITS format =

Most users, however, will prefer to work with spectrogram (frequency-time) and image data, which are also outputs of the pipeline system shown in Figure 1 (orange boxes). Spectrograms are provided as standard FITS tables containing the frequency list, list of times, and data in both total power (TP) and a sum of amplitudes over intermediate-length baselines (cross power or XP). Likewise, image data products are in FITS format with standard keywords and are converted into the Helioprojective Cartesian coordinate system compatible with the World Coordinate System (WCS) convention, along with correct registration for the spatial, spectral, and temporal coordinates. Both the spectrogram and image data products are calibrated properly and have physical radio intensity units (sfu for spectrograms and brightness temperature for radio images).

We provide the following data products:
* Synoptic products:
** All-day total-power spectrograms:
** All-day cross-power spectrograms:
** All-day synoptic images:
* Event-based products:
** Flare spectrograms: These are full time and frequency resolution spectrograms produced from the median of calibrated cross-power visibilities in FITS format, cropped to cover the flare duration. Pre-flare background is also subtracted. Compared to total-power spectrograms, these spectrograms have the advantage of revealing details of the flare evolution by "filtering out" the large-scale, continuous background from the visibilities (as they are poorly correlated by baselines with intermediate lengths). Note that for flares that have a large source size, the flux shown by the cross-power spectrograms can be lower than its true flux (as a fraction of the flux will be "resolved out"). In this case, one might compare the spectrograms with our total-power spectrogram products.
** Pipeline-produced spectral images: We also have a semi-automated flare imaging pipeline to produce calibrated (and self-calibrated) images at 12-s cadence in up to 10 frequency bands. They are saved in standard FITS format and have been registered into Helioprojective coordinates. They can be read by SSWIDL or astropy/sunpy. These data have already been calibrated to physical units and are usually good to be compared with context data. But please be cautious when using them for quantitative spectral analysis.

'''List of Level 1 data products currently provided'''
{| class="wikitable"
|-
! scope="col"| Category
! scope="col"| Data Product
! scope="col"| Naming Convention
! scope="col"| Download Link
|-
! rowspan="2" | Synoptic Spectrograms
| All-day TP Spectrograms
| EOVSA_TPall_yyyymmdd.fts
!rowspan="9" | https://ovsa.njit.edu/browser
|-
| All-day XP Spectrograms
| EOVSA_XPall_yyyymmdd.fts
|-
! rowspan="7" | Synoptic Images
|-
| Synoptic 1.4 GHz images
| eovsa_yyyymmdd.spw00-01.tb.disk.fits
|-
| Synoptic 3.0 GHz images
| eovsa_yyyymmdd.spw02-05.tb.disk.fits
|-
| Synoptic 4.5 GHz images
| eovsa_yyyymmdd.spw06-10.tb.disk.fits
|-
| Synoptic 6.8 GHz images
| eovsa_yyyymmdd.spw11-20.tb.disk.fits
|-
| Synoptic 10.2 GHz images
| eovsa_yyyymmdd.spw21-30.tb.disk.fits
|-
| Synoptic 13.9 GHz images
| eovsa_yyyymmdd.spw31-43.tb.disk.fits
|-
! rowspan="1" | Flare Spectrograms
| Full-resolution cross-power Spectrogram
| eovsa.spec.flare_id_YYYYMMDDHHMMSS.fits
!rowspan="2" | https://ovsa.njit.edu/flarelist
|-
! rowspan="1" | Flare Spectral Images
| Pipeline-produced spectral images
| eovsa.lev1_mbd_12s.YYYY-MM-DDTHHMMSSZ.image.fits
|-
|}

==Browsing and Downloading level 1 data==
[[File:eovsa_browser.jpg|right|thumb|EOVSA Browser]]
[[file:EOVSA_flarelist.jpg|right|thumb|EOVSA Flare List]]
===Synoptic level 1 data===
EOVSA Level 1 synoptic data products can be retrieved with the following steps:
* Go to [http://ovsa.njit.edu/browser/ EOVSA browser] page.
* Browse to the date of interest.
* Click "synoptic fits" button next to the calendar tool.
* Select the data product based on the names listed in the table above.

===Flare level 1 data===
EOVSA flare list with spectrograms and spectral images can be queried and downloaded at https://ovsa.njit.edu/flarelist. Users can use the top box to select a time range of interest and query our flare list. The results are displayed in the dropdown box. An interactive plot of the flare light curves will be shown at the bottom of the page once an event is highlighted (by clicking on the flare ID). Quicklook plots and FITS files of the spectrograms and flare movies can be accessed by clicking the icons in each flare record.

==Reading level 1 data==
===Software===
We have developed a package for EOVSA data processing and analysis:
[https://github.com/suncasa/suncasa SunCASA] A wrapper around [https://casa.nrao.edu/ CASA (the Common Astronomy Software Applications package)] for synthesis imaging and visualizing solar spectral imaging data. CASA is one of the leading software tools for "supporting the data post-processing needs of the next generation of radio astronomical telescopes such as ALMA and VLA", an international effort led by the [https://public.nrao.edu/ National Radio Astronomy Observatory]. The current version of CASA uses Python (2.7) interface. More information about CASA can be found on [https://casa.nrao.edu/ NRAO's CASA website ]. Note, CASA is available ONLY on UNIX-BASED PLATFORMS (and therefore, so is SunCASA). We are developing a new version of SunCASA based on CASA 6 (which offers a modular approach) so that users have the flexibility to build CASA tools and tasks in their Python environment.

Please [http://www.ovsa.njit.edu/wiki/index.php/SunCASA_Installation follow this link] for details regarding the installation of SunCASA on your own machine (only available on Unix-bases OS). This will take you to another page.

===Flare Spectrograms and Multi-Frequency Images ===
* An example of how to read and plot these FITS data in Python (with Astropy and SunPy) can be accessed at [https://colab.research.google.com/drive/1Y3ONWCxLPYvWda5_LqFNxafJtwZDNJBD?usp=sharing#scrollTo=ueiMoHbdxfo- this Google Colab Jupyter notebook].
* We are working on an example with SSWIDL and will release it soon.

===All-day TP spectrum===
Daily total power full-Sun-integrated spectrogram calibrated in solar flux units are provided at 451 frequencies (134 frequencies prior to 2019 Feb 22) and 1 s time resolution.

To read a spectrogram file in Python using the suncasa library:

<pre style="background-color: #FCEBD9;">
from suncasa.eovsa import eovsa_dspec as ds
from astropy.time import Time
from matplotlib.colors import LogNorm
## Read EOVSA Dynamic Spectrum FITS file <filename>
filename = 'EOVSA_TPall_20170713.fts'
s = ds.get_dspec(filename, doplot=True, cmap='gist_heat', norm=LogNorm(vmax=2.1e3, vmin=40))
## To access the data in the spectrogram object, use
spec = s['spectrogram'] ## (Array of amplitudes in SFU, of size nfreq,ntimes)
fghz = s['spectrum_axis'] ## (Array of frequencies in GHz, of size nfreq)
tim = Time(s['time_axis'], format='mjd') ## (Array of UT times in astropy.time object, of size ntimes)

</pre>

The '''get_dspec''' function is accessible on [https://github.com/suncasa/suncasa-src/blob/master/suncasa/eovsa/eovsa_dspec.py GitHub]. For comprehensive guidance, please refer to suncasa's [https://suncasa-src.readthedocs.io/en/latest/autoapi/suncasa/eovsa/eovsa_dspec/index.html ReadtheDocs page].
[[File:TPSP.jpeg|center|500px]]

The following code will read the spectrogram file in IDL:

<pre style="background-color: #FCEBD9;">
function dspec,filename,doplot=doplot
; Read EOVSA Dynamic Spectrum FITS file <filename> and return a spectrogram object.
; Optionally show an overview plot if doplot switch is set
;
; Usage:
; s = dspec(<filename>) ; Returns spectrogram object
; s = dspec(<filename>,/doplot) ; Plots spectrum and returns spectrogram object
;
; To access the data in the spectrogram object, use
; spec = s.get(/spectrogram) (Array of amplitudes in SFU, of size ntimes, nfreq)
; fghz = s.get(/spectrum_axis) (Array of frequencies in GHz, of size nfreq)
; ut = s.get(/time_axis) (Array of UT times in anytim format, of size ntimes)

default,doplot,0
spec = mrdfits(filename,0)
freq = mrdfits(filename,1)
time = mrdfits(filename,2)
fghz = freq.sfreq
ut = anytim(time)
s = spectrogram(spec,ut,fghz)
if doplot then begin
window,/free,xsiz=1024,ysiz=600
; Find min and max of data from 5% to 95% of sorted array (eliminates outliers)
sarr = sort(spec)
dlim = minmax(spec[sarr[n_elements(sarr)*0.05:n_elements(sarr)*0.95]])
; Set drange with margin factor of 2 on low end and 5 on high end
s.set,drange=dlim*[0.5,5]
loadct,3
s.plot,/log,/xsty,/ysty,ytitle='Frequency [GHz]',charsize=1.5
endif
return,s
end
</pre>
[[File:IDL_TPSP.png|center|500px]]

===Synoptic 6-band Images===
Full disk images at 6 selected frequency bands centered at 1.4, 3.0, 4.5, 6.8, 10.2, and 13.9 GHz are provided once per day, calibrated in brightness temperature. [[File:synoptic_image.jpg| center |400px]]

The EOVSA full disk image FITS files are compressed with the RICE algorithm implemented in the FITS file handling module (astropy.io.fits) in Astropy. EOVSA FITS files are very similar to the compressed SDO/AIA FITS files from JSOC. Popular coding languages can easily read compressed images directly.

In IDL, you can use read_sdo in the ONTOLOGY package, which should be installed by default in SolarSoftWare (SSW), to read compressed EOVSA FITS files. The following code will read the EOVSA image FITS file in SSWIDL:

<pre style="background-color: #FCEBD9;">
read_sdo,'eovsa_20191225.spw11-20.tb.disk.fits',header,data,/UNCOMP_DELETE
index2map,header,data,eomap
plot_map,eomap
</pre>

[[File:eovsa_20191225_image_sswidl.jpg| center |250px]]

In Python, you can use SunPy map module to read EOVAS FITS files. SunPy is an open solar data analysis environment for Python. The installation instruction can be found at [https://sunpy.org/ SunPy official website].
<pre style="background-color: #FCEBD9;">
import matplotlib.pyplot as plt
from sunpy import map as smap
eofile='eovsa_20191225.spw11-20.tb.disk.fits'
eomap = smap.Map(eofile)
eomap.plot()
plt.show()
</pre>
[[File:eovsa_20191225_image_py.jpg| center |250px]]

Although the Sunpy Python package already exists for doing analysis of solar data, it has a significant learning curve and lacks the generality of the Mapping routines written by Dominic Zarro for the IDL-based Solarsoft (SSW). We provided IDL Mapping routines available in Python that may help those IDL users who have been avoiding learning Python. '''The mapping routines work equally well in both Python 2.7 and Python 3'''.
Get the [http://www.ovsa.njit.edu/wiki/index.php/Mapping_Software Mapping routines]
The following code will read the EOVSA image FITS file in python:
<pre style="background-color: #FCEBD9;">
from mapping.plot_map import plot_map
from mapping.fits2map import fits2map
eofile='eovsa_20191225.spw11-20.tb.disk.fits'
eomap, h = fits2map(eofile,header=True)
plot_map(eomap, grid=15, limb=True,cmap='gray')
</pre>
[[File:eovsa_20191225_image_py_ssw-mapping.jpg| center |250px]]

EOVSA Data Products

2024-03-29T14:26:03Z

Binchen:

=Introduction=
EOVSA observes the full disk of the Sun at all times when the Sun is >10 degrees above the local horizon (season dependent and ranges from 7-12 hours duration centered on 20 UT). EOVSA records data at 451 science frequency channels each second, in four polarization products, as well as additional total flux measurements from each individual antenna. Raw data in the visibility domain are processed through a pipeline processing system to produce images and spectrograms in the time- and frequency-dependent image plane (the block diagram in Figure 1 shows the data flow in the pipeline).
[[File:pipeline_flowchart.jpg|center|600px|EOVSA pipeline block diagram/flow chart ]]

We deliver the radio interferometry data on the following three levels:

=Level 0 - Raw visibility data from the instrument=

As outlined in Figure 1, EOVSA creates raw data products in the left-hand column (labeled Level 0). This includes observations of cosmic sources for phase calibration, and gain and pointing observations required for total power calibration.

==Raw "Interim" Database (IDB) visibility data==
Full-resolution raw "Interim" Database (IDB) visibility data. They are stored in Miriad format, and hence may not be that useful for most people. Be patient after clicking the link--this is a very long list of directories, one for each available date. These data can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/IDB/

==Raw 1-min-averaged visibility data==
This is the same as for the IDB data, except with 1-minute time integration applied. This is typically not useful for flares, but is perfectly fine for imaging active regions and full Sun. These data can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/UDB/

=Level 0.5 - Calibrated visibility data=
After applying calibration and other preliminary processing to the raw (level 0) data, we create the CASA ms’s in the second column in Figure 1 (labeled "level 0.5"). These visibility data are in the Fourier domain of the true images in the plane of the sky and are not immediately ready for spectral imaging analysis yet. However, they have all of the required content to produce images and spectrogram data in standard FITS format (level 1.0). We provide a set of standard ms’s for each day (red boxes in Figure 1), for use by researchers who know how to deal with visibility data.

==Calibrated full-resolution visibility data for flare events==
Calibrated and self-calibrated visibility data for flare events (purple boxes in Figure 1) will typically be available within 7 days after they are taken. They will be released at our flare list site soon: https://ovsa.njit.edu/flarelist

==Self-calibrated 1-min-averaged visibility data==
EOVSA 1-min averaged visibility data in CASA ms format can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/UDBms_slfcaled

=Level 1.0 - Images and spectrogram data in standard FITS format =

Most users, however, will prefer to work with spectrogram (frequency-time) and image data, which are also outputs of the pipeline system shown in Figure 1 (orange boxes). Spectrograms are provided as standard FITS tables containing the frequency list, list of times, and data in both total power (TP) and a sum of amplitudes over intermediate-length baselines (cross power or XP). Likewise, image data products are in FITS format with standard keywords and are converted into the Helioprojective Cartesian coordinate system compatible with the World Coordinate System (WCS) convention, along with correct registration for the spatial, spectral, and temporal coordinates. Both the spectrogram and image data products are calibrated properly and have physical radio intensity units (sfu for spectrograms and brightness temperature for radio images).

We provide the following data products:
* Synoptic products:
** All-day total-power spectrograms:
** All-day cross-power spectrograms:
** All-day synoptic images:
* Event-based products:
** Flare spectrograms: These are full time and frequency resolution spectrograms produced from the median of calibrated cross-power visibilities in FITS format, cropped to cover the flare duration. Pre-flare background is also subtracted. Compared to total-power spectrograms, these spectrograms have the advantage of revealing details of the flare evolution by "filtering out" the large-scale, continuous background from the visibilities (as they are poorly correlated by baselines with intermediate lengths). Note that for flares that have a large source size, the flux shown by the cross-power spectrograms can be lower than its true flux (as a fraction of the flux will be "resolved out"). In this case, one might compare the spectrograms with our total-power spectrogram products.
** Pipeline-produced spectral images: We also have a semi-automated flare imaging pipeline to produce calibrated (and self-calibrated) images at 12-s cadence in up to 10 frequency bands. They are saved in standard FITS format and have been registered into Helioprojective coordinates. They can be read by SSWIDL or astropy/sunpy. These data have already been calibrated to physical units and are usually good to be compared with context data. But please be cautious when using them for quantitative spectral analysis.

'''List of Level 1 data products currently provided'''
{| class="wikitable"
|-
! scope="col"| Category
! scope="col"| Data Product
! scope="col"| Naming Convention
! scope="col"| Download Link
|-
! rowspan="2" | Synoptic Spectrograms
| All-day TP Spectrograms
| EOVSA_TPall_yyyymmdd.fts
!rowspan="9" | https://ovsa.njit.edu/browser
|-
| All-day XP Spectrograms
| EOVSA_XPall_yyyymmdd.fts
|-
! rowspan="7" | Synoptic Images
|-
| Synoptic 1.4 GHz images
| eovsa_yyyymmdd.spw00-01.tb.disk.fits
|-
| Synoptic 3.0 GHz images
| eovsa_yyyymmdd.spw02-05.tb.disk.fits
|-
| Synoptic 4.5 GHz images
| eovsa_yyyymmdd.spw06-10.tb.disk.fits
|-
| Synoptic 6.8 GHz images
| eovsa_yyyymmdd.spw11-20.tb.disk.fits
|-
| Synoptic 10.2 GHz images
| eovsa_yyyymmdd.spw21-30.tb.disk.fits
|-
| Synoptic 13.9 GHz images
| eovsa_yyyymmdd.spw31-43.tb.disk.fits
|-
! rowspan="1" | Flare Spectrograms
| Full-resolution cross-power Spectrogram
| eovsa.spec.flare_id_YYYYMMDDHHMMSS.fits
!rowspan="2" | https://ovsa.njit.edu/flarelist
|-
! rowspan="1" | Flare Spectral Images
| Pipeline-produced spectral images
| eovsa.lev1_mbd_12s.YYYY-MM-DDTHHMMSSZ.image.fits
|-
|}

==Browsing and Downloading level 1 data==
[[File:eovsa_browser.jpg|right|thumb|EOVSA Browser]]
[[file:EOVSA_flarelist.jpg|right|thumb|EOVSA Flare List]]
===Synoptic level 1 data===
EOVSA Level 1 synoptic data products can be retrieved with the following steps:
* Go to [http://ovsa.njit.edu/browser/ EOVSA browser] page.
* Browse to the date of interest.
* Click "synoptic fits" button next to the calendar tool.
* Select the data product based on the names listed in the table above.

===Flare level 1 data===
EOVSA flare list with spectrograms and spectral images can be queried and downloaded at https://ovsa.njit.edu/flarelist. Users can use the top box to select a time range of interest and query our flare list. The results are displayed in the dropdown box. An interactive plot of the flare light curves will be shown at the bottom of the page once an event is highlighted (by clicking on the flare ID). Quicklook plots and FITS files of the spectrograms and flare movies can be accessed by clicking the icons in each flare record.

==Reading level 1 data==
===Software===
We have developed a package for EOVSA data processing and analysis:
[https://github.com/suncasa/suncasa SunCASA] A wrapper around [https://casa.nrao.edu/ CASA (the Common Astronomy Software Applications package)] for synthesis imaging and visualizing solar spectral imaging data. CASA is one of the leading software tools for "supporting the data post-processing needs of the next generation of radio astronomical telescopes such as ALMA and VLA", an international effort led by the [https://public.nrao.edu/ National Radio Astronomy Observatory]. The current version of CASA uses Python (2.7) interface. More information about CASA can be found on [https://casa.nrao.edu/ NRAO's CASA website ]. Note, CASA is available ONLY on UNIX-BASED PLATFORMS (and therefore, so is SunCASA). We are developing a new version of SunCASA based on CASA 6 (which offers a modular approach) so that users have the flexibility to build CASA tools and tasks in their Python environment.

Please [http://www.ovsa.njit.edu/wiki/index.php/SunCASA_Installation follow this link] for details regarding the installation of SunCASA on your own machine (only available on Unix-bases OS). This will take you to another page.

===Flare Spectrograms and Multi-Frequency Images ===
* An example of how to read and plot these FITS data in Python (with Astropy and SunPy) can be accessed at [https://colab.research.google.com/drive/1Y3ONWCxLPYvWda5_LqFNxafJtwZDNJBD?usp=sharing#scrollTo=ueiMoHbdxfo- this Google Colab Jupyter notebook].
* We are working on an example with SSWIDL and will release it soon.

===All-day TP spectrum===
Daily total power full-Sun-integrated spectrogram calibrated in solar flux units are provided at 451 frequencies (134 frequencies prior to 2019 Feb 22) and 1 s time resolution.

To read a spectrogram file in Python using the suncasa library:

<pre style="background-color: #FCEBD9;">
from suncasa.eovsa import eovsa_dspec as ds
from astropy.time import Time
from matplotlib.colors import LogNorm
## Read EOVSA Dynamic Spectrum FITS file <filename>
filename = 'EOVSA_TPall_20170713.fts'
s = ds.get_dspec(filename, doplot=True, cmap='gist_heat', norm=LogNorm(vmax=2.1e3, vmin=40))
## To access the data in the spectrogram object, use
spec = s['spectrogram'] ## (Array of amplitudes in SFU, of size nfreq,ntimes)
fghz = s['spectrum_axis'] ## (Array of frequencies in GHz, of size nfreq)
tim = Time(s['time_axis'], format='mjd') ## (Array of UT times in astropy.time object, of size ntimes)

</pre>

The '''get_dspec''' function is accessible on [https://github.com/suncasa/suncasa-src/blob/master/suncasa/eovsa/eovsa_dspec.py GitHub]. For comprehensive guidance, please refer to suncasa's [https://suncasa-src.readthedocs.io/en/latest/autoapi/suncasa/eovsa/eovsa_dspec/index.html ReadtheDocs page].
[[File:TPSP.jpeg|center|500px]]

The following code will read the spectrogram file in IDL:

<pre style="background-color: #FCEBD9;">
function dspec,filename,doplot=doplot
; Read EOVSA Dynamic Spectrum FITS file <filename> and return a spectrogram object.
; Optionally show an overview plot if doplot switch is set
;
; Usage:
; s = dspec(<filename>) ; Returns spectrogram object
; s = dspec(<filename>,/doplot) ; Plots spectrum and returns spectrogram object
;
; To access the data in the spectrogram object, use
; spec = s.get(/spectrogram) (Array of amplitudes in SFU, of size ntimes, nfreq)
; fghz = s.get(/spectrum_axis) (Array of frequencies in GHz, of size nfreq)
; ut = s.get(/time_axis) (Array of UT times in anytim format, of size ntimes)

default,doplot,0
spec = mrdfits(filename,0)
freq = mrdfits(filename,1)
time = mrdfits(filename,2)
fghz = freq.sfreq
ut = anytim(time)
s = spectrogram(spec,ut,fghz)
if doplot then begin
window,/free,xsiz=1024,ysiz=600
; Find min and max of data from 5% to 95% of sorted array (eliminates outliers)
sarr = sort(spec)
dlim = minmax(spec[sarr[n_elements(sarr)*0.05:n_elements(sarr)*0.95]])
; Set drange with margin factor of 2 on low end and 5 on high end
s.set,drange=dlim*[0.5,5]
loadct,3
s.plot,/log,/xsty,/ysty,ytitle='Frequency [GHz]',charsize=1.5
endif
return,s
end
</pre>
[[File:IDL_TPSP.png|center|500px]]

===Synoptic 6-band Images===
Full disk images at 6 selected frequency bands centered at 1.4, 3.0, 4.5, 6.8, 10.2, and 13.9 GHz are provided once per day, calibrated in brightness temperature. [[File:synoptic_image.jpg| center |400px]]

The EOVSA full disk image FITS files are compressed with the RICE algorithm implemented in the FITS file handling module (astropy.io.fits) in Astropy. EOVSA FITS files are very similar to the compressed SDO/AIA FITS files from JSOC. Popular coding languages can easily read compressed images directly.

In IDL, you can use read_sdo in the ONTOLOGY package, which should be installed by default in SolarSoftWare (SSW), to read compressed EOVSA FITS files. The following code will read the EOVSA image FITS file in SSWIDL:

<pre style="background-color: #FCEBD9;">
read_sdo,'eovsa_20191225.spw11-20.tb.disk.fits',header,data,/UNCOMP_DELETE
index2map,header,data,eomap
plot_map,eomap
</pre>

[[File:eovsa_20191225_image_sswidl.jpg| center |250px]]

In Python, you can use SunPy map module to read EOVAS FITS files. SunPy is an open solar data analysis environment for Python. The installation instruction can be found at [https://sunpy.org/ SunPy official website].
<pre style="background-color: #FCEBD9;">
import matplotlib.pyplot as plt
from sunpy import map as smap
eofile='eovsa_20191225.spw11-20.tb.disk.fits'
eomap = smap.Map(eofile)
eomap.plot()
plt.show()
</pre>
[[File:eovsa_20191225_image_py.jpg| center |250px]]

Although the Sunpy Python package already exists for doing analysis of solar data, it has a significant learning curve and lacks the generality of the Mapping routines written by Dominic Zarro for the IDL-based Solarsoft (SSW). We provided IDL Mapping routines available in Python that may help those IDL users who have been avoiding learning Python. '''The mapping routines work equally well in both Python 2.7 and Python 3'''.
Get the [http://www.ovsa.njit.edu/wiki/index.php/Mapping_Software Mapping routines]
The following code will read the EOVSA image FITS file in python:
<pre style="background-color: #FCEBD9;">
from mapping.plot_map import plot_map
from mapping.fits2map import fits2map
eofile='eovsa_20191225.spw11-20.tb.disk.fits'
eomap, h = fits2map(eofile,header=True)
plot_map(eomap, grid=15, limb=True,cmap='gray')
</pre>
[[File:eovsa_20191225_image_py_ssw-mapping.jpg| center |250px]]

EOVSA Data Products

2024-03-29T14:25:19Z

Binchen: /* Flare level 1 data */

EOVSA observes the full disk of the Sun at all times when the Sun is >10 degrees above the local horizon (season dependent and ranges from 7-12 hours duration centered on 20 UT). EOVSA records data at 451 science frequency channels each second, in four polarization products, as well as additional total flux measurements from each individual antenna. Raw data in the visibility domain are processed through a pipeline processing system to produce images and spectrograms in the time- and frequency-dependent image plane (the block diagram in Figure 1 shows the data flow in the pipeline).
[[File:pipeline_flowchart.jpg|center|600px|EOVSA pipeline block diagram/flow chart ]]

We deliver the radio interferometry data on the following three levels:

=Level 0 - Raw visibility data from the instrument=

As outlined in Figure 1, EOVSA creates raw data products in the left-hand column (labeled Level 0). This includes observations of cosmic sources for phase calibration, and gain and pointing observations required for total power calibration.

==Raw "Interim" Database (IDB) visibility data==
Full-resolution raw "Interim" Database (IDB) visibility data. They are stored in Miriad format, and hence may not be that useful for most people. Be patient after clicking the link--this is a very long list of directories, one for each available date. These data can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/IDB/

==Raw 1-min-averaged visibility data==
This is the same as for the IDB data, except with 1-minute time integration applied. This is typically not useful for flares, but is perfectly fine for imaging active regions and full Sun. These data can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/UDB/

=Level 0.5 - Calibrated visibility data=
After applying calibration and other preliminary processing to the raw (level 0) data, we create the CASA ms’s in the second column in Figure 1 (labeled "level 0.5"). These visibility data are in the Fourier domain of the true images in the plane of the sky and are not immediately ready for spectral imaging analysis yet. However, they have all of the required content to produce images and spectrogram data in standard FITS format (level 1.0). We provide a set of standard ms’s for each day (red boxes in Figure 1), for use by researchers who know how to deal with visibility data.

==Calibrated full-resolution visibility data for flare events==
Calibrated and self-calibrated visibility data for flare events (purple boxes in Figure 1) will typically be available within 7 days after they are taken. They will be released at our flare list site soon: https://ovsa.njit.edu/flarelist

==Self-calibrated 1-min-averaged visibility data==
EOVSA 1-min averaged visibility data in CASA ms format can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/UDBms_slfcaled

=Level 1.0 - Images and spectrogram data in standard FITS format =

Most users, however, will prefer to work with spectrogram (frequency-time) and image data, which are also outputs of the pipeline system shown in Figure 1 (orange boxes). Spectrograms are provided as standard FITS tables containing the frequency list, list of times, and data in both total power (TP) and a sum of amplitudes over intermediate-length baselines (cross power or XP). Likewise, image data products are in FITS format with standard keywords and are converted into the Helioprojective Cartesian coordinate system compatible with the World Coordinate System (WCS) convention, along with correct registration for the spatial, spectral, and temporal coordinates. Both the spectrogram and image data products are calibrated properly and have physical radio intensity units (sfu for spectrograms and brightness temperature for radio images).

We provide the following data products:
* Synoptic products:
** All-day total-power spectrograms:
** All-day cross-power spectrograms:
** All-day synoptic images:
* Event-based products:
** Flare spectrograms: These are full time and frequency resolution spectrograms produced from the median of calibrated cross-power visibilities in FITS format, cropped to cover the flare duration. Pre-flare background is also subtracted. Compared to total-power spectrograms, these spectrograms have the advantage of revealing details of the flare evolution by "filtering out" the large-scale, continuous background from the visibilities (as they are poorly correlated by baselines with intermediate lengths). Note that for flares that have a large source size, the flux shown by the cross-power spectrograms can be lower than its true flux (as a fraction of the flux will be "resolved out"). In this case, one might compare the spectrograms with our total-power spectrogram products.
** Pipeline-produced spectral images: We also have a semi-automated flare imaging pipeline to produce calibrated (and self-calibrated) images at 12-s cadence in up to 10 frequency bands. They are saved in standard FITS format and have been registered into Helioprojective coordinates. They can be read by SSWIDL or astropy/sunpy. These data have already been calibrated to physical units and are usually good to be compared with context data. But please be cautious when using them for quantitative spectral analysis.

'''List of Level 1 data products currently provided'''
{| class="wikitable"
|-
! scope="col"| Category
! scope="col"| Data Product
! scope="col"| Naming Convention
! scope="col"| Download Link
|-
! rowspan="2" | Synoptic Spectrograms
| All-day TP Spectrograms
| EOVSA_TPall_yyyymmdd.fts
!rowspan="9" | https://ovsa.njit.edu/browser
|-
| All-day XP Spectrograms
| EOVSA_XPall_yyyymmdd.fts
|-
! rowspan="7" | Synoptic Images
|-
| Synoptic 1.4 GHz images
| eovsa_yyyymmdd.spw00-01.tb.disk.fits
|-
| Synoptic 3.0 GHz images
| eovsa_yyyymmdd.spw02-05.tb.disk.fits
|-
| Synoptic 4.5 GHz images
| eovsa_yyyymmdd.spw06-10.tb.disk.fits
|-
| Synoptic 6.8 GHz images
| eovsa_yyyymmdd.spw11-20.tb.disk.fits
|-
| Synoptic 10.2 GHz images
| eovsa_yyyymmdd.spw21-30.tb.disk.fits
|-
| Synoptic 13.9 GHz images
| eovsa_yyyymmdd.spw31-43.tb.disk.fits
|-
! rowspan="1" | Flare Spectrograms
| Full-resolution cross-power Spectrogram
| eovsa.spec.flare_id_YYYYMMDDHHMMSS.fits
!rowspan="2" | https://ovsa.njit.edu/flarelist
|-
! rowspan="1" | Flare Spectral Images
| Pipeline-produced spectral images
| eovsa.lev1_mbd_12s.YYYY-MM-DDTHHMMSSZ.image.fits
|-
|}

==Browsing and Downloading level 1 data==
[[File:eovsa_browser.jpg|right|thumb|EOVSA Browser]]
[[file:EOVSA_flarelist.jpg|right|thumb|EOVSA Flare List]]
===Synoptic level 1 data===
EOVSA Level 1 synoptic data products can be retrieved with the following steps:
* Go to [http://ovsa.njit.edu/browser/ EOVSA browser] page.
* Browse to the date of interest.
* Click "synoptic fits" button next to the calendar tool.
* Select the data product based on the names listed in the table above.

===Flare level 1 data===
EOVSA flare list with spectrograms and spectral images can be queried and downloaded at https://ovsa.njit.edu/flarelist. Users can use the top box to select a time range of interest and query our flare list. The results are displayed in the dropdown box. An interactive plot of the flare light curves will be shown at the bottom of the page once an event is highlighted (by clicking on the flare ID). Quicklook plots and FITS files of the spectrograms and flare movies can be accessed by clicking the icons in each flare record.

==Reading level 1 data==
===Software===
We have developed a package for EOVSA data processing and analysis:
[https://github.com/suncasa/suncasa SunCASA] A wrapper around [https://casa.nrao.edu/ CASA (the Common Astronomy Software Applications package)] for synthesis imaging and visualizing solar spectral imaging data. CASA is one of the leading software tools for "supporting the data post-processing needs of the next generation of radio astronomical telescopes such as ALMA and VLA", an international effort led by the [https://public.nrao.edu/ National Radio Astronomy Observatory]. The current version of CASA uses Python (2.7) interface. More information about CASA can be found on [https://casa.nrao.edu/ NRAO's CASA website ]. Note, CASA is available ONLY on UNIX-BASED PLATFORMS (and therefore, so is SunCASA). We are developing a new version of SunCASA based on CASA 6 (which offers a modular approach) so that users have the flexibility to build CASA tools and tasks in their Python environment.

Please [http://www.ovsa.njit.edu/wiki/index.php/SunCASA_Installation follow this link] for details regarding the installation of SunCASA on your own machine (only available on Unix-bases OS). This will take you to another page.

===Flare Spectrograms and Multi-Frequency Images ===
* An example of how to read and plot these FITS data in Python (with Astropy and SunPy) can be accessed at [https://colab.research.google.com/drive/1Y3ONWCxLPYvWda5_LqFNxafJtwZDNJBD?usp=sharing#scrollTo=ueiMoHbdxfo- this Google Colab Jupyter notebook].
* We are working on an example with SSWIDL and will release it soon.

===All-day TP spectrum===
Daily total power full-Sun-integrated spectrogram calibrated in solar flux units are provided at 451 frequencies (134 frequencies prior to 2019 Feb 22) and 1 s time resolution.

To read a spectrogram file in Python using the suncasa library:

<pre style="background-color: #FCEBD9;">
from suncasa.eovsa import eovsa_dspec as ds
from astropy.time import Time
from matplotlib.colors import LogNorm
## Read EOVSA Dynamic Spectrum FITS file <filename>
filename = 'EOVSA_TPall_20170713.fts'
s = ds.get_dspec(filename, doplot=True, cmap='gist_heat', norm=LogNorm(vmax=2.1e3, vmin=40))
## To access the data in the spectrogram object, use
spec = s['spectrogram'] ## (Array of amplitudes in SFU, of size nfreq,ntimes)
fghz = s['spectrum_axis'] ## (Array of frequencies in GHz, of size nfreq)
tim = Time(s['time_axis'], format='mjd') ## (Array of UT times in astropy.time object, of size ntimes)

</pre>

The '''get_dspec''' function is accessible on [https://github.com/suncasa/suncasa-src/blob/master/suncasa/eovsa/eovsa_dspec.py GitHub]. For comprehensive guidance, please refer to suncasa's [https://suncasa-src.readthedocs.io/en/latest/autoapi/suncasa/eovsa/eovsa_dspec/index.html ReadtheDocs page].
[[File:TPSP.jpeg|center|500px]]

The following code will read the spectrogram file in IDL:

<pre style="background-color: #FCEBD9;">
function dspec,filename,doplot=doplot
; Read EOVSA Dynamic Spectrum FITS file <filename> and return a spectrogram object.
; Optionally show an overview plot if doplot switch is set
;
; Usage:
; s = dspec(<filename>) ; Returns spectrogram object
; s = dspec(<filename>,/doplot) ; Plots spectrum and returns spectrogram object
;
; To access the data in the spectrogram object, use
; spec = s.get(/spectrogram) (Array of amplitudes in SFU, of size ntimes, nfreq)
; fghz = s.get(/spectrum_axis) (Array of frequencies in GHz, of size nfreq)
; ut = s.get(/time_axis) (Array of UT times in anytim format, of size ntimes)

default,doplot,0
spec = mrdfits(filename,0)
freq = mrdfits(filename,1)
time = mrdfits(filename,2)
fghz = freq.sfreq
ut = anytim(time)
s = spectrogram(spec,ut,fghz)
if doplot then begin
window,/free,xsiz=1024,ysiz=600
; Find min and max of data from 5% to 95% of sorted array (eliminates outliers)
sarr = sort(spec)
dlim = minmax(spec[sarr[n_elements(sarr)*0.05:n_elements(sarr)*0.95]])
; Set drange with margin factor of 2 on low end and 5 on high end
s.set,drange=dlim*[0.5,5]
loadct,3
s.plot,/log,/xsty,/ysty,ytitle='Frequency [GHz]',charsize=1.5
endif
return,s
end
</pre>
[[File:IDL_TPSP.png|center|500px]]

===Synoptic 6-band Images===
Full disk images at 6 selected frequency bands centered at 1.4, 3.0, 4.5, 6.8, 10.2, and 13.9 GHz are provided once per day, calibrated in brightness temperature. [[File:synoptic_image.jpg| center |400px]]

The EOVSA full disk image FITS files are compressed with the RICE algorithm implemented in the FITS file handling module (astropy.io.fits) in Astropy. EOVSA FITS files are very similar to the compressed SDO/AIA FITS files from JSOC. Popular coding languages can easily read compressed images directly.

In IDL, you can use read_sdo in the ONTOLOGY package, which should be installed by default in SolarSoftWare (SSW), to read compressed EOVSA FITS files. The following code will read the EOVSA image FITS file in SSWIDL:

<pre style="background-color: #FCEBD9;">
read_sdo,'eovsa_20191225.spw11-20.tb.disk.fits',header,data,/UNCOMP_DELETE
index2map,header,data,eomap
plot_map,eomap
</pre>

[[File:eovsa_20191225_image_sswidl.jpg| center |250px]]

In Python, you can use SunPy map module to read EOVAS FITS files. SunPy is an open solar data analysis environment for Python. The installation instruction can be found at [https://sunpy.org/ SunPy official website].
<pre style="background-color: #FCEBD9;">
import matplotlib.pyplot as plt
from sunpy import map as smap
eofile='eovsa_20191225.spw11-20.tb.disk.fits'
eomap = smap.Map(eofile)
eomap.plot()
plt.show()
</pre>
[[File:eovsa_20191225_image_py.jpg| center |250px]]

Although the Sunpy Python package already exists for doing analysis of solar data, it has a significant learning curve and lacks the generality of the Mapping routines written by Dominic Zarro for the IDL-based Solarsoft (SSW). We provided IDL Mapping routines available in Python that may help those IDL users who have been avoiding learning Python. '''The mapping routines work equally well in both Python 2.7 and Python 3'''.
Get the [http://www.ovsa.njit.edu/wiki/index.php/Mapping_Software Mapping routines]
The following code will read the EOVSA image FITS file in python:
<pre style="background-color: #FCEBD9;">
from mapping.plot_map import plot_map
from mapping.fits2map import fits2map
eofile='eovsa_20191225.spw11-20.tb.disk.fits'
eomap, h = fits2map(eofile,header=True)
plot_map(eomap, grid=15, limb=True,cmap='gray')
</pre>
[[File:eovsa_20191225_image_py_ssw-mapping.jpg| center |250px]]

File:EOVSA flarelist.jpg

2024-03-29T14:23:02Z

Binchen: Binchen uploaded a new version of File:EOVSA flarelist.jpg

== Summary ==
Snapshot of EOVSA flare list

EOVSA Data Products

2024-03-29T14:22:24Z

Binchen: /* Getting level 1 data */

EOVSA observes the full disk of the Sun at all times when the Sun is >10 degrees above the local horizon (season dependent and ranges from 7-12 hours duration centered on 20 UT). EOVSA records data at 451 science frequency channels each second, in four polarization products, as well as additional total flux measurements from each individual antenna. Raw data in the visibility domain are processed through a pipeline processing system to produce images and spectrograms in the time- and frequency-dependent image plane (the block diagram in Figure 1 shows the data flow in the pipeline).
[[File:pipeline_flowchart.jpg|center|600px|EOVSA pipeline block diagram/flow chart ]]

We deliver the radio interferometry data on the following three levels:

=Level 0 - Raw visibility data from the instrument=

As outlined in Figure 1, EOVSA creates raw data products in the left-hand column (labeled Level 0). This includes observations of cosmic sources for phase calibration, and gain and pointing observations required for total power calibration.

==Raw "Interim" Database (IDB) visibility data==
Full-resolution raw "Interim" Database (IDB) visibility data. They are stored in Miriad format, and hence may not be that useful for most people. Be patient after clicking the link--this is a very long list of directories, one for each available date. These data can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/IDB/

==Raw 1-min-averaged visibility data==
This is the same as for the IDB data, except with 1-minute time integration applied. This is typically not useful for flares, but is perfectly fine for imaging active regions and full Sun. These data can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/UDB/

=Level 0.5 - Calibrated visibility data=
After applying calibration and other preliminary processing to the raw (level 0) data, we create the CASA ms’s in the second column in Figure 1 (labeled "level 0.5"). These visibility data are in the Fourier domain of the true images in the plane of the sky and are not immediately ready for spectral imaging analysis yet. However, they have all of the required content to produce images and spectrogram data in standard FITS format (level 1.0). We provide a set of standard ms’s for each day (red boxes in Figure 1), for use by researchers who know how to deal with visibility data.

==Calibrated full-resolution visibility data for flare events==
Calibrated and self-calibrated visibility data for flare events (purple boxes in Figure 1) will typically be available within 7 days after they are taken. They will be released at our flare list site soon: https://ovsa.njit.edu/flarelist

==Self-calibrated 1-min-averaged visibility data==
EOVSA 1-min averaged visibility data in CASA ms format can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/UDBms_slfcaled

=Level 1.0 - Images and spectrogram data in standard FITS format =

Most users, however, will prefer to work with spectrogram (frequency-time) and image data, which are also outputs of the pipeline system shown in Figure 1 (orange boxes). Spectrograms are provided as standard FITS tables containing the frequency list, list of times, and data in both total power (TP) and a sum of amplitudes over intermediate-length baselines (cross power or XP). Likewise, image data products are in FITS format with standard keywords and are converted into the Helioprojective Cartesian coordinate system compatible with the World Coordinate System (WCS) convention, along with correct registration for the spatial, spectral, and temporal coordinates. Both the spectrogram and image data products are calibrated properly and have physical radio intensity units (sfu for spectrograms and brightness temperature for radio images).

We provide the following data products:
* Synoptic products:
** All-day total-power spectrograms:
** All-day cross-power spectrograms:
** All-day synoptic images:
* Event-based products:
** Flare spectrograms: These are full time and frequency resolution spectrograms produced from the median of calibrated cross-power visibilities in FITS format, cropped to cover the flare duration. Pre-flare background is also subtracted. Compared to total-power spectrograms, these spectrograms have the advantage of revealing details of the flare evolution by "filtering out" the large-scale, continuous background from the visibilities (as they are poorly correlated by baselines with intermediate lengths). Note that for flares that have a large source size, the flux shown by the cross-power spectrograms can be lower than its true flux (as a fraction of the flux will be "resolved out"). In this case, one might compare the spectrograms with our total-power spectrogram products.
** Pipeline-produced spectral images: We also have a semi-automated flare imaging pipeline to produce calibrated (and self-calibrated) images at 12-s cadence in up to 10 frequency bands. They are saved in standard FITS format and have been registered into Helioprojective coordinates. They can be read by SSWIDL or astropy/sunpy. These data have already been calibrated to physical units and are usually good to be compared with context data. But please be cautious when using them for quantitative spectral analysis.

'''List of Level 1 data products currently provided'''
{| class="wikitable"
|-
! scope="col"| Category
! scope="col"| Data Product
! scope="col"| Naming Convention
! scope="col"| Download Link
|-
! rowspan="2" | Synoptic Spectrograms
| All-day TP Spectrograms
| EOVSA_TPall_yyyymmdd.fts
!rowspan="9" | https://ovsa.njit.edu/browser
|-
| All-day XP Spectrograms
| EOVSA_XPall_yyyymmdd.fts
|-
! rowspan="7" | Synoptic Images
|-
| Synoptic 1.4 GHz images
| eovsa_yyyymmdd.spw00-01.tb.disk.fits
|-
| Synoptic 3.0 GHz images
| eovsa_yyyymmdd.spw02-05.tb.disk.fits
|-
| Synoptic 4.5 GHz images
| eovsa_yyyymmdd.spw06-10.tb.disk.fits
|-
| Synoptic 6.8 GHz images
| eovsa_yyyymmdd.spw11-20.tb.disk.fits
|-
| Synoptic 10.2 GHz images
| eovsa_yyyymmdd.spw21-30.tb.disk.fits
|-
| Synoptic 13.9 GHz images
| eovsa_yyyymmdd.spw31-43.tb.disk.fits
|-
! rowspan="1" | Flare Spectrograms
| Full-resolution cross-power Spectrogram
| eovsa.spec.flare_id_YYYYMMDDHHMMSS.fits
!rowspan="2" | https://ovsa.njit.edu/flarelist
|-
! rowspan="1" | Flare Spectral Images
| Pipeline-produced spectral images
| eovsa.lev1_mbd_12s.YYYY-MM-DDTHHMMSSZ.image.fits
|-
|}

==Browsing and Downloading level 1 data==
[[File:eovsa_browser.jpg|right|thumb|EOVSA Browser]]
[[file:EOVSA_flarelist.jpg|right|thumb|EOVSA Flare List]]
===Synoptic level 1 data===
EOVSA Level 1 synoptic data products can be retrieved with the following steps:
* Go to [http://ovsa.njit.edu/browser/ EOVSA browser] page.
* Browse to the date of interest.
* Click "synoptic fits" button next to the calendar tool.
* Select the data product based on the names listed in the table above.

===Flare level 1 data===
EOVSA flare list with spectrograms and spectral images can be queried and downloaded at https://ovsa.njit.edu/flarelist. Users can use the top box to select a time range of interest and query our flare list. The results are displayed in the dropdown box.

==Reading level 1 data==
===Software===
We have developed a package for EOVSA data processing and analysis:
[https://github.com/suncasa/suncasa SunCASA] A wrapper around [https://casa.nrao.edu/ CASA (the Common Astronomy Software Applications package)] for synthesis imaging and visualizing solar spectral imaging data. CASA is one of the leading software tools for "supporting the data post-processing needs of the next generation of radio astronomical telescopes such as ALMA and VLA", an international effort led by the [https://public.nrao.edu/ National Radio Astronomy Observatory]. The current version of CASA uses Python (2.7) interface. More information about CASA can be found on [https://casa.nrao.edu/ NRAO's CASA website ]. Note, CASA is available ONLY on UNIX-BASED PLATFORMS (and therefore, so is SunCASA). We are developing a new version of SunCASA based on CASA 6 (which offers a modular approach) so that users have the flexibility to build CASA tools and tasks in their Python environment.

Please [http://www.ovsa.njit.edu/wiki/index.php/SunCASA_Installation follow this link] for details regarding the installation of SunCASA on your own machine (only available on Unix-bases OS). This will take you to another page.

===Flare Spectrograms and Multi-Frequency Images ===
* An example of how to read and plot these FITS data in Python (with Astropy and SunPy) can be accessed at [https://colab.research.google.com/drive/1Y3ONWCxLPYvWda5_LqFNxafJtwZDNJBD?usp=sharing#scrollTo=ueiMoHbdxfo- this Google Colab Jupyter notebook].
* We are working on an example with SSWIDL and will release it soon.

===All-day TP spectrum===
Daily total power full-Sun-integrated spectrogram calibrated in solar flux units are provided at 451 frequencies (134 frequencies prior to 2019 Feb 22) and 1 s time resolution.

To read a spectrogram file in Python using the suncasa library:

<pre style="background-color: #FCEBD9;">
from suncasa.eovsa import eovsa_dspec as ds
from astropy.time import Time
from matplotlib.colors import LogNorm
## Read EOVSA Dynamic Spectrum FITS file <filename>
filename = 'EOVSA_TPall_20170713.fts'
s = ds.get_dspec(filename, doplot=True, cmap='gist_heat', norm=LogNorm(vmax=2.1e3, vmin=40))
## To access the data in the spectrogram object, use
spec = s['spectrogram'] ## (Array of amplitudes in SFU, of size nfreq,ntimes)
fghz = s['spectrum_axis'] ## (Array of frequencies in GHz, of size nfreq)
tim = Time(s['time_axis'], format='mjd') ## (Array of UT times in astropy.time object, of size ntimes)

</pre>

The '''get_dspec''' function is accessible on [https://github.com/suncasa/suncasa-src/blob/master/suncasa/eovsa/eovsa_dspec.py GitHub]. For comprehensive guidance, please refer to suncasa's [https://suncasa-src.readthedocs.io/en/latest/autoapi/suncasa/eovsa/eovsa_dspec/index.html ReadtheDocs page].
[[File:TPSP.jpeg|center|500px]]

The following code will read the spectrogram file in IDL:

<pre style="background-color: #FCEBD9;">
function dspec,filename,doplot=doplot
; Read EOVSA Dynamic Spectrum FITS file <filename> and return a spectrogram object.
; Optionally show an overview plot if doplot switch is set
;
; Usage:
; s = dspec(<filename>) ; Returns spectrogram object
; s = dspec(<filename>,/doplot) ; Plots spectrum and returns spectrogram object
;
; To access the data in the spectrogram object, use
; spec = s.get(/spectrogram) (Array of amplitudes in SFU, of size ntimes, nfreq)
; fghz = s.get(/spectrum_axis) (Array of frequencies in GHz, of size nfreq)
; ut = s.get(/time_axis) (Array of UT times in anytim format, of size ntimes)

default,doplot,0
spec = mrdfits(filename,0)
freq = mrdfits(filename,1)
time = mrdfits(filename,2)
fghz = freq.sfreq
ut = anytim(time)
s = spectrogram(spec,ut,fghz)
if doplot then begin
window,/free,xsiz=1024,ysiz=600
; Find min and max of data from 5% to 95% of sorted array (eliminates outliers)
sarr = sort(spec)
dlim = minmax(spec[sarr[n_elements(sarr)*0.05:n_elements(sarr)*0.95]])
; Set drange with margin factor of 2 on low end and 5 on high end
s.set,drange=dlim*[0.5,5]
loadct,3
s.plot,/log,/xsty,/ysty,ytitle='Frequency [GHz]',charsize=1.5
endif
return,s
end
</pre>
[[File:IDL_TPSP.png|center|500px]]

===Synoptic 6-band Images===
Full disk images at 6 selected frequency bands centered at 1.4, 3.0, 4.5, 6.8, 10.2, and 13.9 GHz are provided once per day, calibrated in brightness temperature. [[File:synoptic_image.jpg| center |400px]]

The EOVSA full disk image FITS files are compressed with the RICE algorithm implemented in the FITS file handling module (astropy.io.fits) in Astropy. EOVSA FITS files are very similar to the compressed SDO/AIA FITS files from JSOC. Popular coding languages can easily read compressed images directly.

In IDL, you can use read_sdo in the ONTOLOGY package, which should be installed by default in SolarSoftWare (SSW), to read compressed EOVSA FITS files. The following code will read the EOVSA image FITS file in SSWIDL:

<pre style="background-color: #FCEBD9;">
read_sdo,'eovsa_20191225.spw11-20.tb.disk.fits',header,data,/UNCOMP_DELETE
index2map,header,data,eomap
plot_map,eomap
</pre>

[[File:eovsa_20191225_image_sswidl.jpg| center |250px]]

In Python, you can use SunPy map module to read EOVAS FITS files. SunPy is an open solar data analysis environment for Python. The installation instruction can be found at [https://sunpy.org/ SunPy official website].
<pre style="background-color: #FCEBD9;">
import matplotlib.pyplot as plt
from sunpy import map as smap
eofile='eovsa_20191225.spw11-20.tb.disk.fits'
eomap = smap.Map(eofile)
eomap.plot()
plt.show()
</pre>
[[File:eovsa_20191225_image_py.jpg| center |250px]]

Although the Sunpy Python package already exists for doing analysis of solar data, it has a significant learning curve and lacks the generality of the Mapping routines written by Dominic Zarro for the IDL-based Solarsoft (SSW). We provided IDL Mapping routines available in Python that may help those IDL users who have been avoiding learning Python. '''The mapping routines work equally well in both Python 2.7 and Python 3'''.
Get the [http://www.ovsa.njit.edu/wiki/index.php/Mapping_Software Mapping routines]
The following code will read the EOVSA image FITS file in python:
<pre style="background-color: #FCEBD9;">
from mapping.plot_map import plot_map
from mapping.fits2map import fits2map
eofile='eovsa_20191225.spw11-20.tb.disk.fits'
eomap, h = fits2map(eofile,header=True)
plot_map(eomap, grid=15, limb=True,cmap='gray')
</pre>
[[File:eovsa_20191225_image_py_ssw-mapping.jpg| center |250px]]

EOVSA Data Products

2024-03-29T14:15:59Z

Binchen: /* Getting level 1 data */

EOVSA observes the full disk of the Sun at all times when the Sun is >10 degrees above the local horizon (season dependent and ranges from 7-12 hours duration centered on 20 UT). EOVSA records data at 451 science frequency channels each second, in four polarization products, as well as additional total flux measurements from each individual antenna. Raw data in the visibility domain are processed through a pipeline processing system to produce images and spectrograms in the time- and frequency-dependent image plane (the block diagram in Figure 1 shows the data flow in the pipeline).
[[File:pipeline_flowchart.jpg|center|600px|EOVSA pipeline block diagram/flow chart ]]

We deliver the radio interferometry data on the following three levels:

=Level 0 - Raw visibility data from the instrument=

As outlined in Figure 1, EOVSA creates raw data products in the left-hand column (labeled Level 0). This includes observations of cosmic sources for phase calibration, and gain and pointing observations required for total power calibration.

==Raw "Interim" Database (IDB) visibility data==
Full-resolution raw "Interim" Database (IDB) visibility data. They are stored in Miriad format, and hence may not be that useful for most people. Be patient after clicking the link--this is a very long list of directories, one for each available date. These data can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/IDB/

==Raw 1-min-averaged visibility data==
This is the same as for the IDB data, except with 1-minute time integration applied. This is typically not useful for flares, but is perfectly fine for imaging active regions and full Sun. These data can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/UDB/

=Level 0.5 - Calibrated visibility data=
After applying calibration and other preliminary processing to the raw (level 0) data, we create the CASA ms’s in the second column in Figure 1 (labeled "level 0.5"). These visibility data are in the Fourier domain of the true images in the plane of the sky and are not immediately ready for spectral imaging analysis yet. However, they have all of the required content to produce images and spectrogram data in standard FITS format (level 1.0). We provide a set of standard ms’s for each day (red boxes in Figure 1), for use by researchers who know how to deal with visibility data.

==Calibrated full-resolution visibility data for flare events==
Calibrated and self-calibrated visibility data for flare events (purple boxes in Figure 1) will typically be available within 7 days after they are taken. They will be released at our flare list site soon: https://ovsa.njit.edu/flarelist

==Self-calibrated 1-min-averaged visibility data==
EOVSA 1-min averaged visibility data in CASA ms format can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/UDBms_slfcaled

=Level 1.0 - Images and spectrogram data in standard FITS format =

Most users, however, will prefer to work with spectrogram (frequency-time) and image data, which are also outputs of the pipeline system shown in Figure 1 (orange boxes). Spectrograms are provided as standard FITS tables containing the frequency list, list of times, and data in both total power (TP) and a sum of amplitudes over intermediate-length baselines (cross power or XP). Likewise, image data products are in FITS format with standard keywords and are converted into the Helioprojective Cartesian coordinate system compatible with the World Coordinate System (WCS) convention, along with correct registration for the spatial, spectral, and temporal coordinates. Both the spectrogram and image data products are calibrated properly and have physical radio intensity units (sfu for spectrograms and brightness temperature for radio images).

We provide the following data products:
* Synoptic products:
** All-day total-power spectrograms:
** All-day cross-power spectrograms:
** All-day synoptic images:
* Event-based products:
** Flare spectrograms: These are full time and frequency resolution spectrograms produced from the median of calibrated cross-power visibilities in FITS format, cropped to cover the flare duration. Pre-flare background is also subtracted. Compared to total-power spectrograms, these spectrograms have the advantage of revealing details of the flare evolution by "filtering out" the large-scale, continuous background from the visibilities (as they are poorly correlated by baselines with intermediate lengths). Note that for flares that have a large source size, the flux shown by the cross-power spectrograms can be lower than its true flux (as a fraction of the flux will be "resolved out"). In this case, one might compare the spectrograms with our total-power spectrogram products.
** Pipeline-produced spectral images: We also have a semi-automated flare imaging pipeline to produce calibrated (and self-calibrated) images at 12-s cadence in up to 10 frequency bands. They are saved in standard FITS format and have been registered into Helioprojective coordinates. They can be read by SSWIDL or astropy/sunpy. These data have already been calibrated to physical units and are usually good to be compared with context data. But please be cautious when using them for quantitative spectral analysis.

'''List of Level 1 data products currently provided'''
{| class="wikitable"
|-
! scope="col"| Category
! scope="col"| Data Product
! scope="col"| Naming Convention
! scope="col"| Download Link
|-
! rowspan="2" | Synoptic Spectrograms
| All-day TP Spectrograms
| EOVSA_TPall_yyyymmdd.fts
!rowspan="9" | https://ovsa.njit.edu/browser
|-
| All-day XP Spectrograms
| EOVSA_XPall_yyyymmdd.fts
|-
! rowspan="7" | Synoptic Images
|-
| Synoptic 1.4 GHz images
| eovsa_yyyymmdd.spw00-01.tb.disk.fits
|-
| Synoptic 3.0 GHz images
| eovsa_yyyymmdd.spw02-05.tb.disk.fits
|-
| Synoptic 4.5 GHz images
| eovsa_yyyymmdd.spw06-10.tb.disk.fits
|-
| Synoptic 6.8 GHz images
| eovsa_yyyymmdd.spw11-20.tb.disk.fits
|-
| Synoptic 10.2 GHz images
| eovsa_yyyymmdd.spw21-30.tb.disk.fits
|-
| Synoptic 13.9 GHz images
| eovsa_yyyymmdd.spw31-43.tb.disk.fits
|-
! rowspan="1" | Flare Spectrograms
| Full-resolution cross-power Spectrogram
| eovsa.spec.flare_id_YYYYMMDDHHMMSS.fits
!rowspan="2" | https://ovsa.njit.edu/flarelist
|-
! rowspan="1" | Flare Spectral Images
| Pipeline-produced spectral images
| eovsa.lev1_mbd_12s.YYYY-MM-DDTHHMMSSZ.image.fits
|-
|}

==Getting level 1 data==
===Synoptic level 1 data===
EOVSA Level 1 synoptic data products can be retrieved with the following steps:
* Go to [http://ovsa.njit.edu/browser/ EOVSA browser] page.
* Browse to the date of interest.
* Click "synoptic fits" button next to the calendar tool.
* Select the data product based on the names listed in the table above.
[[File:eovsa_browser.jpg|600px|center]]

===Flare level 1 data===
EOVSA flare list with spectrograms and spectral images can be queried and downloaded at https://ovsa.njit.edu/flarelist.
[[file:EOVSA_flarelist.jpg|600px|center]]

==Reading level 1 data==
===Software===
We have developed a package for EOVSA data processing and analysis:
[https://github.com/suncasa/suncasa SunCASA] A wrapper around [https://casa.nrao.edu/ CASA (the Common Astronomy Software Applications package)] for synthesis imaging and visualizing solar spectral imaging data. CASA is one of the leading software tools for "supporting the data post-processing needs of the next generation of radio astronomical telescopes such as ALMA and VLA", an international effort led by the [https://public.nrao.edu/ National Radio Astronomy Observatory]. The current version of CASA uses Python (2.7) interface. More information about CASA can be found on [https://casa.nrao.edu/ NRAO's CASA website ]. Note, CASA is available ONLY on UNIX-BASED PLATFORMS (and therefore, so is SunCASA). We are developing a new version of SunCASA based on CASA 6 (which offers a modular approach) so that users have the flexibility to build CASA tools and tasks in their Python environment.

Please [http://www.ovsa.njit.edu/wiki/index.php/SunCASA_Installation follow this link] for details regarding the installation of SunCASA on your own machine (only available on Unix-bases OS). This will take you to another page.

===Flare Spectrograms and Multi-Frequency Images ===
* An example of how to read and plot these FITS data in Python (with Astropy and SunPy) can be accessed at [https://colab.research.google.com/drive/1Y3ONWCxLPYvWda5_LqFNxafJtwZDNJBD?usp=sharing#scrollTo=ueiMoHbdxfo- this Google Colab Jupyter notebook].
* We are working on an example with SSWIDL and will release it soon.

===All-day TP spectrum===
Daily total power full-Sun-integrated spectrogram calibrated in solar flux units are provided at 451 frequencies (134 frequencies prior to 2019 Feb 22) and 1 s time resolution.

To read a spectrogram file in Python using the suncasa library:

<pre style="background-color: #FCEBD9;">
from suncasa.eovsa import eovsa_dspec as ds
from astropy.time import Time
from matplotlib.colors import LogNorm
## Read EOVSA Dynamic Spectrum FITS file <filename>
filename = 'EOVSA_TPall_20170713.fts'
s = ds.get_dspec(filename, doplot=True, cmap='gist_heat', norm=LogNorm(vmax=2.1e3, vmin=40))
## To access the data in the spectrogram object, use
spec = s['spectrogram'] ## (Array of amplitudes in SFU, of size nfreq,ntimes)
fghz = s['spectrum_axis'] ## (Array of frequencies in GHz, of size nfreq)
tim = Time(s['time_axis'], format='mjd') ## (Array of UT times in astropy.time object, of size ntimes)

</pre>

The '''get_dspec''' function is accessible on [https://github.com/suncasa/suncasa-src/blob/master/suncasa/eovsa/eovsa_dspec.py GitHub]. For comprehensive guidance, please refer to suncasa's [https://suncasa-src.readthedocs.io/en/latest/autoapi/suncasa/eovsa/eovsa_dspec/index.html ReadtheDocs page].
[[File:TPSP.jpeg|center|500px]]

The following code will read the spectrogram file in IDL:

<pre style="background-color: #FCEBD9;">
function dspec,filename,doplot=doplot
; Read EOVSA Dynamic Spectrum FITS file <filename> and return a spectrogram object.
; Optionally show an overview plot if doplot switch is set
;
; Usage:
; s = dspec(<filename>) ; Returns spectrogram object
; s = dspec(<filename>,/doplot) ; Plots spectrum and returns spectrogram object
;
; To access the data in the spectrogram object, use
; spec = s.get(/spectrogram) (Array of amplitudes in SFU, of size ntimes, nfreq)
; fghz = s.get(/spectrum_axis) (Array of frequencies in GHz, of size nfreq)
; ut = s.get(/time_axis) (Array of UT times in anytim format, of size ntimes)

default,doplot,0
spec = mrdfits(filename,0)
freq = mrdfits(filename,1)
time = mrdfits(filename,2)
fghz = freq.sfreq
ut = anytim(time)
s = spectrogram(spec,ut,fghz)
if doplot then begin
window,/free,xsiz=1024,ysiz=600
; Find min and max of data from 5% to 95% of sorted array (eliminates outliers)
sarr = sort(spec)
dlim = minmax(spec[sarr[n_elements(sarr)*0.05:n_elements(sarr)*0.95]])
; Set drange with margin factor of 2 on low end and 5 on high end
s.set,drange=dlim*[0.5,5]
loadct,3
s.plot,/log,/xsty,/ysty,ytitle='Frequency [GHz]',charsize=1.5
endif
return,s
end
</pre>
[[File:IDL_TPSP.png|center|500px]]

===Synoptic 6-band Images===
Full disk images at 6 selected frequency bands centered at 1.4, 3.0, 4.5, 6.8, 10.2, and 13.9 GHz are provided once per day, calibrated in brightness temperature. [[File:synoptic_image.jpg| center |400px]]

The EOVSA full disk image FITS files are compressed with the RICE algorithm implemented in the FITS file handling module (astropy.io.fits) in Astropy. EOVSA FITS files are very similar to the compressed SDO/AIA FITS files from JSOC. Popular coding languages can easily read compressed images directly.

In IDL, you can use read_sdo in the ONTOLOGY package, which should be installed by default in SolarSoftWare (SSW), to read compressed EOVSA FITS files. The following code will read the EOVSA image FITS file in SSWIDL:

<pre style="background-color: #FCEBD9;">
read_sdo,'eovsa_20191225.spw11-20.tb.disk.fits',header,data,/UNCOMP_DELETE
index2map,header,data,eomap
plot_map,eomap
</pre>

[[File:eovsa_20191225_image_sswidl.jpg| center |250px]]

In Python, you can use SunPy map module to read EOVAS FITS files. SunPy is an open solar data analysis environment for Python. The installation instruction can be found at [https://sunpy.org/ SunPy official website].
<pre style="background-color: #FCEBD9;">
import matplotlib.pyplot as plt
from sunpy import map as smap
eofile='eovsa_20191225.spw11-20.tb.disk.fits'
eomap = smap.Map(eofile)
eomap.plot()
plt.show()
</pre>
[[File:eovsa_20191225_image_py.jpg| center |250px]]

Although the Sunpy Python package already exists for doing analysis of solar data, it has a significant learning curve and lacks the generality of the Mapping routines written by Dominic Zarro for the IDL-based Solarsoft (SSW). We provided IDL Mapping routines available in Python that may help those IDL users who have been avoiding learning Python. '''The mapping routines work equally well in both Python 2.7 and Python 3'''.
Get the [http://www.ovsa.njit.edu/wiki/index.php/Mapping_Software Mapping routines]
The following code will read the EOVSA image FITS file in python:
<pre style="background-color: #FCEBD9;">
from mapping.plot_map import plot_map
from mapping.fits2map import fits2map
eofile='eovsa_20191225.spw11-20.tb.disk.fits'
eomap, h = fits2map(eofile,header=True)
plot_map(eomap, grid=15, limb=True,cmap='gray')
</pre>
[[File:eovsa_20191225_image_py_ssw-mapping.jpg| center |250px]]

EOVSA Data Products

2024-03-29T14:15:48Z

Binchen: /* Getting level 1 data */

EOVSA observes the full disk of the Sun at all times when the Sun is >10 degrees above the local horizon (season dependent and ranges from 7-12 hours duration centered on 20 UT). EOVSA records data at 451 science frequency channels each second, in four polarization products, as well as additional total flux measurements from each individual antenna. Raw data in the visibility domain are processed through a pipeline processing system to produce images and spectrograms in the time- and frequency-dependent image plane (the block diagram in Figure 1 shows the data flow in the pipeline).
[[File:pipeline_flowchart.jpg|center|600px|EOVSA pipeline block diagram/flow chart ]]

We deliver the radio interferometry data on the following three levels:

=Level 0 - Raw visibility data from the instrument=

As outlined in Figure 1, EOVSA creates raw data products in the left-hand column (labeled Level 0). This includes observations of cosmic sources for phase calibration, and gain and pointing observations required for total power calibration.

==Raw "Interim" Database (IDB) visibility data==
Full-resolution raw "Interim" Database (IDB) visibility data. They are stored in Miriad format, and hence may not be that useful for most people. Be patient after clicking the link--this is a very long list of directories, one for each available date. These data can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/IDB/

==Raw 1-min-averaged visibility data==
This is the same as for the IDB data, except with 1-minute time integration applied. This is typically not useful for flares, but is perfectly fine for imaging active regions and full Sun. These data can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/UDB/

=Level 0.5 - Calibrated visibility data=
After applying calibration and other preliminary processing to the raw (level 0) data, we create the CASA ms’s in the second column in Figure 1 (labeled "level 0.5"). These visibility data are in the Fourier domain of the true images in the plane of the sky and are not immediately ready for spectral imaging analysis yet. However, they have all of the required content to produce images and spectrogram data in standard FITS format (level 1.0). We provide a set of standard ms’s for each day (red boxes in Figure 1), for use by researchers who know how to deal with visibility data.

==Calibrated full-resolution visibility data for flare events==
Calibrated and self-calibrated visibility data for flare events (purple boxes in Figure 1) will typically be available within 7 days after they are taken. They will be released at our flare list site soon: https://ovsa.njit.edu/flarelist

==Self-calibrated 1-min-averaged visibility data==
EOVSA 1-min averaged visibility data in CASA ms format can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/UDBms_slfcaled

=Level 1.0 - Images and spectrogram data in standard FITS format =

Most users, however, will prefer to work with spectrogram (frequency-time) and image data, which are also outputs of the pipeline system shown in Figure 1 (orange boxes). Spectrograms are provided as standard FITS tables containing the frequency list, list of times, and data in both total power (TP) and a sum of amplitudes over intermediate-length baselines (cross power or XP). Likewise, image data products are in FITS format with standard keywords and are converted into the Helioprojective Cartesian coordinate system compatible with the World Coordinate System (WCS) convention, along with correct registration for the spatial, spectral, and temporal coordinates. Both the spectrogram and image data products are calibrated properly and have physical radio intensity units (sfu for spectrograms and brightness temperature for radio images).

We provide the following data products:
* Synoptic products:
** All-day total-power spectrograms:
** All-day cross-power spectrograms:
** All-day synoptic images:
* Event-based products:
** Flare spectrograms: These are full time and frequency resolution spectrograms produced from the median of calibrated cross-power visibilities in FITS format, cropped to cover the flare duration. Pre-flare background is also subtracted. Compared to total-power spectrograms, these spectrograms have the advantage of revealing details of the flare evolution by "filtering out" the large-scale, continuous background from the visibilities (as they are poorly correlated by baselines with intermediate lengths). Note that for flares that have a large source size, the flux shown by the cross-power spectrograms can be lower than its true flux (as a fraction of the flux will be "resolved out"). In this case, one might compare the spectrograms with our total-power spectrogram products.
** Pipeline-produced spectral images: We also have a semi-automated flare imaging pipeline to produce calibrated (and self-calibrated) images at 12-s cadence in up to 10 frequency bands. They are saved in standard FITS format and have been registered into Helioprojective coordinates. They can be read by SSWIDL or astropy/sunpy. These data have already been calibrated to physical units and are usually good to be compared with context data. But please be cautious when using them for quantitative spectral analysis.

'''List of Level 1 data products currently provided'''
{| class="wikitable"
|-
! scope="col"| Category
! scope="col"| Data Product
! scope="col"| Naming Convention
! scope="col"| Download Link
|-
! rowspan="2" | Synoptic Spectrograms
| All-day TP Spectrograms
| EOVSA_TPall_yyyymmdd.fts
!rowspan="9" | https://ovsa.njit.edu/browser
|-
| All-day XP Spectrograms
| EOVSA_XPall_yyyymmdd.fts
|-
! rowspan="7" | Synoptic Images
|-
| Synoptic 1.4 GHz images
| eovsa_yyyymmdd.spw00-01.tb.disk.fits
|-
| Synoptic 3.0 GHz images
| eovsa_yyyymmdd.spw02-05.tb.disk.fits
|-
| Synoptic 4.5 GHz images
| eovsa_yyyymmdd.spw06-10.tb.disk.fits
|-
| Synoptic 6.8 GHz images
| eovsa_yyyymmdd.spw11-20.tb.disk.fits
|-
| Synoptic 10.2 GHz images
| eovsa_yyyymmdd.spw21-30.tb.disk.fits
|-
| Synoptic 13.9 GHz images
| eovsa_yyyymmdd.spw31-43.tb.disk.fits
|-
! rowspan="1" | Flare Spectrograms
| Full-resolution cross-power Spectrogram
| eovsa.spec.flare_id_YYYYMMDDHHMMSS.fits
!rowspan="2" | https://ovsa.njit.edu/flarelist
|-
! rowspan="1" | Flare Spectral Images
| Pipeline-produced spectral images
| eovsa.lev1_mbd_12s.YYYY-MM-DDTHHMMSSZ.image.fits
|-
|}

==Getting level 1 data==
===Synoptic level 1 data===
EOVSA Level 1 synoptic data products can be retrieved with the following steps:
* Go to [http://ovsa.njit.edu/browser/ EOVSA browser] page.
* Browse to the date of interest.
* Click "synoptic fits" button next to the calendar tool.
* Select the data product based on the names listed in the table above.
[[File:eovsa_browser.jpg|600px|center]]

===Flare level 1 data===
EOVSA flare list with spectrograms and spectral images can be queried and downloaded at https://ovsa.njit.edu/flarelist.
[[file:EOVSA_flarelist.jpg]|600px|center]]

==Reading level 1 data==
===Software===
We have developed a package for EOVSA data processing and analysis:
[https://github.com/suncasa/suncasa SunCASA] A wrapper around [https://casa.nrao.edu/ CASA (the Common Astronomy Software Applications package)] for synthesis imaging and visualizing solar spectral imaging data. CASA is one of the leading software tools for "supporting the data post-processing needs of the next generation of radio astronomical telescopes such as ALMA and VLA", an international effort led by the [https://public.nrao.edu/ National Radio Astronomy Observatory]. The current version of CASA uses Python (2.7) interface. More information about CASA can be found on [https://casa.nrao.edu/ NRAO's CASA website ]. Note, CASA is available ONLY on UNIX-BASED PLATFORMS (and therefore, so is SunCASA). We are developing a new version of SunCASA based on CASA 6 (which offers a modular approach) so that users have the flexibility to build CASA tools and tasks in their Python environment.

Please [http://www.ovsa.njit.edu/wiki/index.php/SunCASA_Installation follow this link] for details regarding the installation of SunCASA on your own machine (only available on Unix-bases OS). This will take you to another page.

===Flare Spectrograms and Multi-Frequency Images ===
* An example of how to read and plot these FITS data in Python (with Astropy and SunPy) can be accessed at [https://colab.research.google.com/drive/1Y3ONWCxLPYvWda5_LqFNxafJtwZDNJBD?usp=sharing#scrollTo=ueiMoHbdxfo- this Google Colab Jupyter notebook].
* We are working on an example with SSWIDL and will release it soon.

===All-day TP spectrum===
Daily total power full-Sun-integrated spectrogram calibrated in solar flux units are provided at 451 frequencies (134 frequencies prior to 2019 Feb 22) and 1 s time resolution.

To read a spectrogram file in Python using the suncasa library:

<pre style="background-color: #FCEBD9;">
from suncasa.eovsa import eovsa_dspec as ds
from astropy.time import Time
from matplotlib.colors import LogNorm
## Read EOVSA Dynamic Spectrum FITS file <filename>
filename = 'EOVSA_TPall_20170713.fts'
s = ds.get_dspec(filename, doplot=True, cmap='gist_heat', norm=LogNorm(vmax=2.1e3, vmin=40))
## To access the data in the spectrogram object, use
spec = s['spectrogram'] ## (Array of amplitudes in SFU, of size nfreq,ntimes)
fghz = s['spectrum_axis'] ## (Array of frequencies in GHz, of size nfreq)
tim = Time(s['time_axis'], format='mjd') ## (Array of UT times in astropy.time object, of size ntimes)

</pre>

The '''get_dspec''' function is accessible on [https://github.com/suncasa/suncasa-src/blob/master/suncasa/eovsa/eovsa_dspec.py GitHub]. For comprehensive guidance, please refer to suncasa's [https://suncasa-src.readthedocs.io/en/latest/autoapi/suncasa/eovsa/eovsa_dspec/index.html ReadtheDocs page].
[[File:TPSP.jpeg|center|500px]]

The following code will read the spectrogram file in IDL:

<pre style="background-color: #FCEBD9;">
function dspec,filename,doplot=doplot
; Read EOVSA Dynamic Spectrum FITS file <filename> and return a spectrogram object.
; Optionally show an overview plot if doplot switch is set
;
; Usage:
; s = dspec(<filename>) ; Returns spectrogram object
; s = dspec(<filename>,/doplot) ; Plots spectrum and returns spectrogram object
;
; To access the data in the spectrogram object, use
; spec = s.get(/spectrogram) (Array of amplitudes in SFU, of size ntimes, nfreq)
; fghz = s.get(/spectrum_axis) (Array of frequencies in GHz, of size nfreq)
; ut = s.get(/time_axis) (Array of UT times in anytim format, of size ntimes)

default,doplot,0
spec = mrdfits(filename,0)
freq = mrdfits(filename,1)
time = mrdfits(filename,2)
fghz = freq.sfreq
ut = anytim(time)
s = spectrogram(spec,ut,fghz)
if doplot then begin
window,/free,xsiz=1024,ysiz=600
; Find min and max of data from 5% to 95% of sorted array (eliminates outliers)
sarr = sort(spec)
dlim = minmax(spec[sarr[n_elements(sarr)*0.05:n_elements(sarr)*0.95]])
; Set drange with margin factor of 2 on low end and 5 on high end
s.set,drange=dlim*[0.5,5]
loadct,3
s.plot,/log,/xsty,/ysty,ytitle='Frequency [GHz]',charsize=1.5
endif
return,s
end
</pre>
[[File:IDL_TPSP.png|center|500px]]

===Synoptic 6-band Images===
Full disk images at 6 selected frequency bands centered at 1.4, 3.0, 4.5, 6.8, 10.2, and 13.9 GHz are provided once per day, calibrated in brightness temperature. [[File:synoptic_image.jpg| center |400px]]

The EOVSA full disk image FITS files are compressed with the RICE algorithm implemented in the FITS file handling module (astropy.io.fits) in Astropy. EOVSA FITS files are very similar to the compressed SDO/AIA FITS files from JSOC. Popular coding languages can easily read compressed images directly.

In IDL, you can use read_sdo in the ONTOLOGY package, which should be installed by default in SolarSoftWare (SSW), to read compressed EOVSA FITS files. The following code will read the EOVSA image FITS file in SSWIDL:

<pre style="background-color: #FCEBD9;">
read_sdo,'eovsa_20191225.spw11-20.tb.disk.fits',header,data,/UNCOMP_DELETE
index2map,header,data,eomap
plot_map,eomap
</pre>

[[File:eovsa_20191225_image_sswidl.jpg| center |250px]]

In Python, you can use SunPy map module to read EOVAS FITS files. SunPy is an open solar data analysis environment for Python. The installation instruction can be found at [https://sunpy.org/ SunPy official website].
<pre style="background-color: #FCEBD9;">
import matplotlib.pyplot as plt
from sunpy import map as smap
eofile='eovsa_20191225.spw11-20.tb.disk.fits'
eomap = smap.Map(eofile)
eomap.plot()
plt.show()
</pre>
[[File:eovsa_20191225_image_py.jpg| center |250px]]

Although the Sunpy Python package already exists for doing analysis of solar data, it has a significant learning curve and lacks the generality of the Mapping routines written by Dominic Zarro for the IDL-based Solarsoft (SSW). We provided IDL Mapping routines available in Python that may help those IDL users who have been avoiding learning Python. '''The mapping routines work equally well in both Python 2.7 and Python 3'''.
Get the [http://www.ovsa.njit.edu/wiki/index.php/Mapping_Software Mapping routines]
The following code will read the EOVSA image FITS file in python:
<pre style="background-color: #FCEBD9;">
from mapping.plot_map import plot_map
from mapping.fits2map import fits2map
eofile='eovsa_20191225.spw11-20.tb.disk.fits'
eomap, h = fits2map(eofile,header=True)
plot_map(eomap, grid=15, limb=True,cmap='gray')
</pre>
[[File:eovsa_20191225_image_py_ssw-mapping.jpg| center |250px]]

EOVSA Data Products

2024-03-29T14:15:33Z

Binchen: /* Flare level 1 data */

EOVSA observes the full disk of the Sun at all times when the Sun is >10 degrees above the local horizon (season dependent and ranges from 7-12 hours duration centered on 20 UT). EOVSA records data at 451 science frequency channels each second, in four polarization products, as well as additional total flux measurements from each individual antenna. Raw data in the visibility domain are processed through a pipeline processing system to produce images and spectrograms in the time- and frequency-dependent image plane (the block diagram in Figure 1 shows the data flow in the pipeline).
[[File:pipeline_flowchart.jpg|center|600px|EOVSA pipeline block diagram/flow chart ]]

We deliver the radio interferometry data on the following three levels:

=Level 0 - Raw visibility data from the instrument=

As outlined in Figure 1, EOVSA creates raw data products in the left-hand column (labeled Level 0). This includes observations of cosmic sources for phase calibration, and gain and pointing observations required for total power calibration.

==Raw "Interim" Database (IDB) visibility data==
Full-resolution raw "Interim" Database (IDB) visibility data. They are stored in Miriad format, and hence may not be that useful for most people. Be patient after clicking the link--this is a very long list of directories, one for each available date. These data can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/IDB/

==Raw 1-min-averaged visibility data==
This is the same as for the IDB data, except with 1-minute time integration applied. This is typically not useful for flares, but is perfectly fine for imaging active regions and full Sun. These data can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/UDB/

=Level 0.5 - Calibrated visibility data=
After applying calibration and other preliminary processing to the raw (level 0) data, we create the CASA ms’s in the second column in Figure 1 (labeled "level 0.5"). These visibility data are in the Fourier domain of the true images in the plane of the sky and are not immediately ready for spectral imaging analysis yet. However, they have all of the required content to produce images and spectrogram data in standard FITS format (level 1.0). We provide a set of standard ms’s for each day (red boxes in Figure 1), for use by researchers who know how to deal with visibility data.

==Calibrated full-resolution visibility data for flare events==
Calibrated and self-calibrated visibility data for flare events (purple boxes in Figure 1) will typically be available within 7 days after they are taken. They will be released at our flare list site soon: https://ovsa.njit.edu/flarelist

==Self-calibrated 1-min-averaged visibility data==
EOVSA 1-min averaged visibility data in CASA ms format can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/UDBms_slfcaled

=Level 1.0 - Images and spectrogram data in standard FITS format =

Most users, however, will prefer to work with spectrogram (frequency-time) and image data, which are also outputs of the pipeline system shown in Figure 1 (orange boxes). Spectrograms are provided as standard FITS tables containing the frequency list, list of times, and data in both total power (TP) and a sum of amplitudes over intermediate-length baselines (cross power or XP). Likewise, image data products are in FITS format with standard keywords and are converted into the Helioprojective Cartesian coordinate system compatible with the World Coordinate System (WCS) convention, along with correct registration for the spatial, spectral, and temporal coordinates. Both the spectrogram and image data products are calibrated properly and have physical radio intensity units (sfu for spectrograms and brightness temperature for radio images).

We provide the following data products:
* Synoptic products:
** All-day total-power spectrograms:
** All-day cross-power spectrograms:
** All-day synoptic images:
* Event-based products:
** Flare spectrograms: These are full time and frequency resolution spectrograms produced from the median of calibrated cross-power visibilities in FITS format, cropped to cover the flare duration. Pre-flare background is also subtracted. Compared to total-power spectrograms, these spectrograms have the advantage of revealing details of the flare evolution by "filtering out" the large-scale, continuous background from the visibilities (as they are poorly correlated by baselines with intermediate lengths). Note that for flares that have a large source size, the flux shown by the cross-power spectrograms can be lower than its true flux (as a fraction of the flux will be "resolved out"). In this case, one might compare the spectrograms with our total-power spectrogram products.
** Pipeline-produced spectral images: We also have a semi-automated flare imaging pipeline to produce calibrated (and self-calibrated) images at 12-s cadence in up to 10 frequency bands. They are saved in standard FITS format and have been registered into Helioprojective coordinates. They can be read by SSWIDL or astropy/sunpy. These data have already been calibrated to physical units and are usually good to be compared with context data. But please be cautious when using them for quantitative spectral analysis.

'''List of Level 1 data products currently provided'''
{| class="wikitable"
|-
! scope="col"| Category
! scope="col"| Data Product
! scope="col"| Naming Convention
! scope="col"| Download Link
|-
! rowspan="2" | Synoptic Spectrograms
| All-day TP Spectrograms
| EOVSA_TPall_yyyymmdd.fts
!rowspan="9" | https://ovsa.njit.edu/browser
|-
| All-day XP Spectrograms
| EOVSA_XPall_yyyymmdd.fts
|-
! rowspan="7" | Synoptic Images
|-
| Synoptic 1.4 GHz images
| eovsa_yyyymmdd.spw00-01.tb.disk.fits
|-
| Synoptic 3.0 GHz images
| eovsa_yyyymmdd.spw02-05.tb.disk.fits
|-
| Synoptic 4.5 GHz images
| eovsa_yyyymmdd.spw06-10.tb.disk.fits
|-
| Synoptic 6.8 GHz images
| eovsa_yyyymmdd.spw11-20.tb.disk.fits
|-
| Synoptic 10.2 GHz images
| eovsa_yyyymmdd.spw21-30.tb.disk.fits
|-
| Synoptic 13.9 GHz images
| eovsa_yyyymmdd.spw31-43.tb.disk.fits
|-
! rowspan="1" | Flare Spectrograms
| Full-resolution cross-power Spectrogram
| eovsa.spec.flare_id_YYYYMMDDHHMMSS.fits
!rowspan="2" | https://ovsa.njit.edu/flarelist
|-
! rowspan="1" | Flare Spectral Images
| Pipeline-produced spectral images
| eovsa.lev1_mbd_12s.YYYY-MM-DDTHHMMSSZ.image.fits
|-
|}

==Getting level 1 data==
===Synoptic level 1 data===
EOVSA Level 1 synoptic data products can be retrieved with the following steps:
* Go to [http://ovsa.njit.edu/browser/ EOVSA browser] page.
* Browse to the date of interest.
* Click "synoptic fits" button next to the calendar tool.
* Select the data product based on the names listed in the table above.
[[File:eovsa_browser.jpg|800px|center]]

===Flare level 1 data===
EOVSA flare list with spectrograms and spectral images can be queried and downloaded at https://ovsa.njit.edu/flarelist.
[[file:EOVSA_flarelist.jpg]]

==Reading level 1 data==
===Software===
We have developed a package for EOVSA data processing and analysis:
[https://github.com/suncasa/suncasa SunCASA] A wrapper around [https://casa.nrao.edu/ CASA (the Common Astronomy Software Applications package)] for synthesis imaging and visualizing solar spectral imaging data. CASA is one of the leading software tools for "supporting the data post-processing needs of the next generation of radio astronomical telescopes such as ALMA and VLA", an international effort led by the [https://public.nrao.edu/ National Radio Astronomy Observatory]. The current version of CASA uses Python (2.7) interface. More information about CASA can be found on [https://casa.nrao.edu/ NRAO's CASA website ]. Note, CASA is available ONLY on UNIX-BASED PLATFORMS (and therefore, so is SunCASA). We are developing a new version of SunCASA based on CASA 6 (which offers a modular approach) so that users have the flexibility to build CASA tools and tasks in their Python environment.

Please [http://www.ovsa.njit.edu/wiki/index.php/SunCASA_Installation follow this link] for details regarding the installation of SunCASA on your own machine (only available on Unix-bases OS). This will take you to another page.

===Flare Spectrograms and Multi-Frequency Images ===
* An example of how to read and plot these FITS data in Python (with Astropy and SunPy) can be accessed at [https://colab.research.google.com/drive/1Y3ONWCxLPYvWda5_LqFNxafJtwZDNJBD?usp=sharing#scrollTo=ueiMoHbdxfo- this Google Colab Jupyter notebook].
* We are working on an example with SSWIDL and will release it soon.

===All-day TP spectrum===
Daily total power full-Sun-integrated spectrogram calibrated in solar flux units are provided at 451 frequencies (134 frequencies prior to 2019 Feb 22) and 1 s time resolution.

To read a spectrogram file in Python using the suncasa library:

<pre style="background-color: #FCEBD9;">
from suncasa.eovsa import eovsa_dspec as ds
from astropy.time import Time
from matplotlib.colors import LogNorm
## Read EOVSA Dynamic Spectrum FITS file <filename>
filename = 'EOVSA_TPall_20170713.fts'
s = ds.get_dspec(filename, doplot=True, cmap='gist_heat', norm=LogNorm(vmax=2.1e3, vmin=40))
## To access the data in the spectrogram object, use
spec = s['spectrogram'] ## (Array of amplitudes in SFU, of size nfreq,ntimes)
fghz = s['spectrum_axis'] ## (Array of frequencies in GHz, of size nfreq)
tim = Time(s['time_axis'], format='mjd') ## (Array of UT times in astropy.time object, of size ntimes)

</pre>

The '''get_dspec''' function is accessible on [https://github.com/suncasa/suncasa-src/blob/master/suncasa/eovsa/eovsa_dspec.py GitHub]. For comprehensive guidance, please refer to suncasa's [https://suncasa-src.readthedocs.io/en/latest/autoapi/suncasa/eovsa/eovsa_dspec/index.html ReadtheDocs page].
[[File:TPSP.jpeg|center|500px]]

The following code will read the spectrogram file in IDL:

<pre style="background-color: #FCEBD9;">
function dspec,filename,doplot=doplot
; Read EOVSA Dynamic Spectrum FITS file <filename> and return a spectrogram object.
; Optionally show an overview plot if doplot switch is set
;
; Usage:
; s = dspec(<filename>) ; Returns spectrogram object
; s = dspec(<filename>,/doplot) ; Plots spectrum and returns spectrogram object
;
; To access the data in the spectrogram object, use
; spec = s.get(/spectrogram) (Array of amplitudes in SFU, of size ntimes, nfreq)
; fghz = s.get(/spectrum_axis) (Array of frequencies in GHz, of size nfreq)
; ut = s.get(/time_axis) (Array of UT times in anytim format, of size ntimes)

default,doplot,0
spec = mrdfits(filename,0)
freq = mrdfits(filename,1)
time = mrdfits(filename,2)
fghz = freq.sfreq
ut = anytim(time)
s = spectrogram(spec,ut,fghz)
if doplot then begin
window,/free,xsiz=1024,ysiz=600
; Find min and max of data from 5% to 95% of sorted array (eliminates outliers)
sarr = sort(spec)
dlim = minmax(spec[sarr[n_elements(sarr)*0.05:n_elements(sarr)*0.95]])
; Set drange with margin factor of 2 on low end and 5 on high end
s.set,drange=dlim*[0.5,5]
loadct,3
s.plot,/log,/xsty,/ysty,ytitle='Frequency [GHz]',charsize=1.5
endif
return,s
end
</pre>
[[File:IDL_TPSP.png|center|500px]]

===Synoptic 6-band Images===
Full disk images at 6 selected frequency bands centered at 1.4, 3.0, 4.5, 6.8, 10.2, and 13.9 GHz are provided once per day, calibrated in brightness temperature. [[File:synoptic_image.jpg| center |400px]]

The EOVSA full disk image FITS files are compressed with the RICE algorithm implemented in the FITS file handling module (astropy.io.fits) in Astropy. EOVSA FITS files are very similar to the compressed SDO/AIA FITS files from JSOC. Popular coding languages can easily read compressed images directly.

In IDL, you can use read_sdo in the ONTOLOGY package, which should be installed by default in SolarSoftWare (SSW), to read compressed EOVSA FITS files. The following code will read the EOVSA image FITS file in SSWIDL:

<pre style="background-color: #FCEBD9;">
read_sdo,'eovsa_20191225.spw11-20.tb.disk.fits',header,data,/UNCOMP_DELETE
index2map,header,data,eomap
plot_map,eomap
</pre>

[[File:eovsa_20191225_image_sswidl.jpg| center |250px]]

In Python, you can use SunPy map module to read EOVAS FITS files. SunPy is an open solar data analysis environment for Python. The installation instruction can be found at [https://sunpy.org/ SunPy official website].
<pre style="background-color: #FCEBD9;">
import matplotlib.pyplot as plt
from sunpy import map as smap
eofile='eovsa_20191225.spw11-20.tb.disk.fits'
eomap = smap.Map(eofile)
eomap.plot()
plt.show()
</pre>
[[File:eovsa_20191225_image_py.jpg| center |250px]]

Although the Sunpy Python package already exists for doing analysis of solar data, it has a significant learning curve and lacks the generality of the Mapping routines written by Dominic Zarro for the IDL-based Solarsoft (SSW). We provided IDL Mapping routines available in Python that may help those IDL users who have been avoiding learning Python. '''The mapping routines work equally well in both Python 2.7 and Python 3'''.
Get the [http://www.ovsa.njit.edu/wiki/index.php/Mapping_Software Mapping routines]
The following code will read the EOVSA image FITS file in python:
<pre style="background-color: #FCEBD9;">
from mapping.plot_map import plot_map
from mapping.fits2map import fits2map
eofile='eovsa_20191225.spw11-20.tb.disk.fits'
eomap, h = fits2map(eofile,header=True)
plot_map(eomap, grid=15, limb=True,cmap='gray')
</pre>
[[File:eovsa_20191225_image_py_ssw-mapping.jpg| center |250px]]

File:EOVSA flarelist.jpg

2024-03-29T14:14:35Z

Binchen: Snapshot of EOVSA flare list

== Summary ==
Snapshot of EOVSA flare list

EOVSA Data Products

2024-03-28T20:30:24Z

Binchen: /* Level 1.0 - Calibrated visibility data */

EOVSA observes the full disk of the Sun at all times when the Sun is >10 degrees above the local horizon (season dependent and ranges from 7-12 hours duration centered on 20 UT). EOVSA records data at 451 science frequency channels each second, in four polarization products, as well as additional total flux measurements from each individual antenna. Raw data in the visibility domain are processed through a pipeline processing system to produce images and spectrograms in the time- and frequency-dependent image plane (the block diagram in Figure 1 shows the data flow in the pipeline).
[[File:pipeline_flowchart.jpg|center|600px|EOVSA pipeline block diagram/flow chart ]]

We deliver the radio interferometry data on the following three levels:

=Level 0 - Raw visibility data from the instrument=

As outlined in Figure 1, EOVSA creates raw data products in the left-hand column (labeled Level 0). This includes observations of cosmic sources for phase calibration, and gain and pointing observations required for total power calibration.

==Raw "Interim" Database (IDB) visibility data==
Full-resolution raw "Interim" Database (IDB) visibility data. They are stored in Miriad format, and hence may not be that useful for most people. Be patient after clicking the link--this is a very long list of directories, one for each available date. These data can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/IDB/

==Raw 1-min-averaged visibility data==
This is the same as for the IDB data, except with 1-minute time integration applied. This is typically not useful for flares, but is perfectly fine for imaging active regions and full Sun. These data can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/UDB/

=Level 0.5 - Calibrated visibility data=
After applying calibration and other preliminary processing to the raw (level 0) data, we create the CASA ms’s in the second column in Figure 1 (labeled "level 0.5"). These visibility data are in the Fourier domain of the true images in the plane of the sky and are not immediately ready for spectral imaging analysis yet. However, they have all of the required content to produce images and spectrogram data in standard FITS format (level 1.0). We provide a set of standard ms’s for each day (red boxes in Figure 1), for use by researchers who know how to deal with visibility data.

==Calibrated full-resolution visibility data for flare events==
EOVSA event data products in boxes with dashed outlines in Figure 1 will typically be available within 7 days after they are taken. We provide the following data products:
* Flare spectrograms: These are full time and frequency resolution spectrograms produced from the median of calibrated cross-power visibilities in FITS format, cropped to cover the flare duration. Pre-flare background is also subtracted. Compared to total-power spectrograms, these spectrograms have the advantage of revealing details of the flare evolution by "filtering out" the large-scale, continuous background from the visibilities (as they are poorly correlated by baselines with intermediate lengths). Note that for flares that have a large source size, the flux shown by the cross-power spectrograms can be lower than its true flux (as a fraction of the flux will be "resolved out"). In this case, one might compare the spectrograms with our total-power spectrogram products.
* Pipeline-produced spectral images: We also have a semi-automated flare imaging pipeline to produce calibrated (and self-calibrated) images at 12-s cadence in up to 10 frequency bands. They are saved

* Link to our EOVSA flare list with spectrograms and spectral images can be queried and downloaded at https://ovsa.njit.edu/flarelist.

* Example of how to read and plot these FITS data in Python (with Astropy and SunPy) can be accessed at [https://colab.research.google.com/drive/1Y3ONWCxLPYvWda5_LqFNxafJtwZDNJBD?usp=sharing#scrollTo=ueiMoHbdxfo- this Google Colab Jupyter notebook].

==Self-calibrated 1-min-averaged visibility data==
EOVSA 1-min averaged visibility data in CASA ms format can be retrieved from the following page:

http://www.ovsa.njit.edu/fits/UDBms_slfcaled

=Level 2.0 - Images and spectrogram data in standard FITS format =

Most users, however, will prefer to work with spectrogram (frequency-time) and image data, which are also outputs of the pipeline system shown in Figure 1 (orange boxes). Spectrograms are provided as standard FITS tables containing the frequency list, list of times, and data in both total power (TP) and a sum of amplitudes over intermediate-length baselines (cross power or XP). Likewise, image data products are in FITS format with standard keywords and are converted into the Helioprojective Cartesian coordinate system compatible with the World Coordinate System (WCS) convention, along with correct registration for the spatial, spectral, and temporal coordinates. Both the spectrogram and image data products are calibrated properly and have physical radio intensity units (sfu for spectrograms and brightness temperature for radio images).

'''List of Level 2 data products'''
{| class="wikitable"
|-
! scope="col"| Category
! scope="col"| Data Product
! scope="col"| Naming Convention
|-
! rowspan="2" | Spectrogram
| All-day TP Spectrogram
| EOVSA_TPall_yyyymmdd.fts
|-
| All-day XP Spectrogram
| EOVSA_XPall_yyyymmdd.fts
|-
! rowspan="7" | Image
|-
| Synoptic 1.4 GHz image
| eovsa_yyyymmdd.spw00-01.tb.disk.fits
|-
| Synoptic 3.0 GHz image
| eovsa_yyyymmdd.spw02-05.tb.disk.fits
|-
| Synoptic 4.5 GHz image
| eovsa_yyyymmdd.spw06-10.tb.disk.fits
|-
| Synoptic 6.8 GHz image
| eovsa_yyyymmdd.spw11-20.tb.disk.fits
|-
| Synoptic 10.2 GHz image
| eovsa_yyyymmdd.spw21-30.tb.disk.fits
|-
| Synoptic 13.9 GHz image
| eovsa_yyyymmdd.spw31-43.tb.disk.fits
|}

==Getting level 2 data==
EOVSA Level 2 data products can be retrieved with the following steps:
* go to [http://ovsa.njit.edu/browser/ EOVSA browser] page.
* Browse to the date of interest.
* Click "synoptic fits" button next to the calendar tool.
* Select the data product based on the names listed in the table above.
[[File:eovsa_browser.jpg|800px|center]]

==Reading level 2 data==
===Software===
We have developed a package for EOVSA data processing and analysis:
[https://github.com/suncasa/suncasa SunCASA] A wrapper around [https://casa.nrao.edu/ CASA (the Common Astronomy Software Applications package)] for synthesis imaging and visualizing solar spectral imaging data. CASA is one of the leading software tools for "supporting the data post-processing needs of the next generation of radio astronomical telescopes such as ALMA and VLA", an international effort led by the [https://public.nrao.edu/ National Radio Astronomy Observatory]. The current version of CASA uses Python (2.7) interface. More information about CASA can be found on [https://casa.nrao.edu/ NRAO's CASA website ]. Note, CASA is available ONLY on UNIX-BASED PLATFORMS (and therefore, so is SunCASA). We are developing a new version of SunCASA based on CASA 6 (which offers a modular approach) so that users have the flexibility to build CASA tools and tasks in their Python environment.

Please [http://www.ovsa.njit.edu/wiki/index.php/SunCASA_Installation follow this link] for details regarding the installation of SunCASA on your own machine (only available on Unix-bases OS). This will take you to another page.

===All-day TP spectrum===
Daily total power full-Sun-integrated spectrogram calibrated in solar flux units are provided at 451 frequencies (134 frequencies prior to 2019 Feb 22) and 1 s time resolution.

To read a spectrogram file in Python using the suncasa library:

<pre style="background-color: #FCEBD9;">
from suncasa.eovsa import eovsa_dspec as ds
from astropy.time import Time
from matplotlib.colors import LogNorm
## Read EOVSA Dynamic Spectrum FITS file <filename>
filename = 'EOVSA_TPall_20170713.fts'
s = ds.get_dspec(filename, doplot=True, cmap='gist_heat', norm=LogNorm(vmax=2.1e3, vmin=40))
## To access the data in the spectrogram object, use
spec = s['spectrogram'] ## (Array of amplitudes in SFU, of size nfreq,ntimes)
fghz = s['spectrum_axis'] ## (Array of frequencies in GHz, of size nfreq)
tim = Time(s['time_axis'], format='mjd') ## (Array of UT times in astropy.time object, of size ntimes)

</pre>

The '''get_dspec''' function is accessible on [https://github.com/suncasa/suncasa-src/blob/master/suncasa/eovsa/eovsa_dspec.py GitHub]. For comprehensive guidance, please refer to suncasa's [https://suncasa-src.readthedocs.io/en/latest/autoapi/suncasa/eovsa/eovsa_dspec/index.html ReadtheDocs page].
[[File:TPSP.jpeg|center|500px]]

The following code will read the spectrogram file in IDL:

<pre style="background-color: #FCEBD9;">
function dspec,filename,doplot=doplot
; Read EOVSA Dynamic Spectrum FITS file <filename> and return a spectrogram object.
; Optionally show an overview plot if doplot switch is set
;
; Usage:
; s = dspec(<filename>) ; Returns spectrogram object
; s = dspec(<filename>,/doplot) ; Plots spectrum and returns spectrogram object
;
; To access the data in the spectrogram object, use
; spec = s.get(/spectrogram) (Array of amplitudes in SFU, of size ntimes, nfreq)
; fghz = s.get(/spectrum_axis) (Array of frequencies in GHz, of size nfreq)
; ut = s.get(/time_axis) (Array of UT times in anytim format, of size ntimes)

default,doplot,0
spec = mrdfits(filename,0)
freq = mrdfits(filename,1)
time = mrdfits(filename,2)
fghz = freq.sfreq
ut = anytim(time)
s = spectrogram(spec,ut,fghz)
if doplot then begin
window,/free,xsiz=1024,ysiz=600
; Find min and max of data from 5% to 95% of sorted array (eliminates outliers)
sarr = sort(spec)
dlim = minmax(spec[sarr[n_elements(sarr)*0.05:n_elements(sarr)*0.95]])
; Set drange with margin factor of 2 on low end and 5 on high end
s.set,drange=dlim*[0.5,5]
loadct,3
s.plot,/log,/xsty,/ysty,ytitle='Frequency [GHz]',charsize=1.5
endif
return,s
end
</pre>
[[File:IDL_TPSP.png|center|500px]]

===Synoptic 6-band Images===
Full disk images at 6 selected frequency bands centered at 1.4, 3.0, 4.5, 6.8, 10.2, and 13.9 GHz are provided once per day, calibrated in brightness temperature. [[File:synoptic_image.jpg| center |400px]]

The EOVSA full disk image FITS files are compressed with the RICE algorithm implemented in the FITS file handling module (astropy.io.fits) in Astropy. EOVSA FITS files are very similar to the compressed SDO/AIA FITS files from JSOC. Popular coding languages can easily read compressed images directly.

In IDL, you can use read_sdo in the ONTOLOGY package, which should be installed by default in SolarSoftWare (SSW), to read compressed EOVSA FITS files. The following code will read the EOVSA image FITS file in SSWIDL:

<pre style="background-color: #FCEBD9;">
read_sdo,'eovsa_20191225.spw11-20.tb.disk.fits',header,data,/UNCOMP_DELETE
index2map,header,data,eomap
plot_map,eomap
</pre>

[[File:eovsa_20191225_image_sswidl.jpg| center |250px]]

In Python, you can use SunPy map module to read EOVAS FITS files. SunPy is an open solar data analysis environment for Python. The installation instruction can be found at [https://sunpy.org/ SunPy official website].
<pre style="background-color: #FCEBD9;">
import matplotlib.pyplot as plt
from sunpy import map as smap
eofile='eovsa_20191225.spw11-20.tb.disk.fits'
eomap = smap.Map(eofile)
eomap.plot()
plt.show()
</pre>
[[File:eovsa_20191225_image_py.jpg| center |250px]]

Although the Sunpy Python package already exists for doing analysis of solar data, it has a significant learning curve and lacks the generality of the Mapping routines written by Dominic Zarro for the IDL-based Solarsoft (SSW). We provided IDL Mapping routines available in Python that may help those IDL users who have been avoiding learning Python. '''The mapping routines work equally well in both Python 2.7 and Python 3'''.
Get the [http://www.ovsa.njit.edu/wiki/index.php/Mapping_Software Mapping routines]
The following code will read the EOVSA image FITS file in python:
<pre style="background-color: #FCEBD9;">
from mapping.plot_map import plot_map
from mapping.fits2map import fits2map
eofile='eovsa_20191225.spw11-20.tb.disk.fits'
eomap, h = fits2map(eofile,header=True)
plot_map(eomap, grid=15, limb=True,cmap='gray')
</pre>
[[File:eovsa_20191225_image_py_ssw-mapping.jpg| center |250px]]

===10-min 6-band Images===
===Event images===