paircars 2.1.11

A package to calibrate MWA solar observation

P-AIRCARS

An automated spectropolarimetric calibration and imaging pipeline designed for solar radio observations using the Murchision Widefield Array (MWA) radio telescope. It performs end-to-end calibration, flagging, and imaging with a focus on dynamic solar data, supporting both spectral and temporal flexibility in imaging products.

Background

Solar radio data presents unique challenges due to the high variability and brightness of the Sun, as well as the need for high time-frequency resolution. The P-AIRCARS pipeline addresses these challenges by:

• Automating the calibration of interferometric data, including flux, phase, and polarization calibrations
• Supporting time-sliced and frequency-sliced imaging workflows
• Leveraging Dask for scalable parallel processing
• Providing hooks for integration with contextual data from other wavelegths for enhanced solar analysis

Documentation

P-AIRCARS documentation is available at: paircars.readthedocs.io

Quickstart

P-AIRCARS is distributed on PyPI. To use it:

1. Create conda environment with python 3.10

   conda create -n paircars_env python=3.10
   conda activate paircars_env
   

2. Install P-AIRCARS in conda environment

   pip install paircars
   

3. Initiate necessary metadata and prefect server

   init-paircars-setup --init --prefect_server
   

4. Before running the pipeline, setup your data as following:

   -- Create a <target_datadir> and put all coarse channel measurement sets of solar scan of a single observation ID (OBSID) inside it.

   -- Create a <cal_datadir> and put all coarse channel measurement sets for calibrator observation of a single OBSID inside it.

5. Run P-AIRCARS pipeline

   run-mwa-paircars <path of target measurement set directory> <path of target metafits file> --cal_datadir <path of calibrator measurement set directory> --cal_metafits <path of calibrator metafits> --workdir <path of work directory> --outdir <path of output products directory>
   

   N.B.: Keep target measurement sets for a single OBSID and calibrator measurement sets for a single OBSID must be kept in seperate directories. If calibrator is not present, do not provide these information.

That's all. You started P-AIRCARS pipeline for analysing your MWA solar observation 🎉.

6. To see all running P-AIRCARS jobs

   show-paircars-status --show
   

7. To see prefect dashboard (only work if you started prefect server)

   run-mwa-mwalogger
   

8. If you did not start prefect server, see local log of any job using the

   run-mwa-mwalogger --jobid <jobid>
   

9. Output products will be saved in : <path of output products directory>

Sample dataset

User can download and test entire P-AIRCARS pipeline using the sample dataset available in Zenodo: https://doi.org/10.5281/zenodo.18641232. Do not use this sample dataset for any publication without permission from the developer.

Acknowledgements

P-AIRCARS is developed by Devojyoti Kansabanik (NCRA-TIFR, Pune, India and CPAESS-UCAR, Boulder, USA) and Surajt Mondal (NCRA-TIFR, Pune, India) and an incarnation of AIRCARS. If you use P-AIRCARS for analysing your MWA solar observations, include the following statement in your paper, and cite the following papers:

This MWA solar observations are analysed using P-AIRCARS pipeline. 

1. Cite P-AIRCARS software in zenodo: https://doi.org/10.5281/zenodo.18625477

2. Kansabanik et al., 2025, ApJS, v278:26

3. Kansabanik et al., 2023, ApJS, v264:47

4. Kansabanik et al., 2022, ApJ, v932:110

5. Kansbanik 2022, Solar Physics, v297:122

6. Mondal et al., 2019, ApJ, v875:97

If you use observations before 2015, include this additonal statement and citation:

Flux calibration of the observations are done using the menthod described in the following paper.

7. Kansabanik et al., 2022, ApJ, v927:17

P-AIRCARS name is given by Dr. Barnali Das (NCRA-TIFR, Pune, India)

License

This project is licensed under the MIT License.