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.
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
P-AIRCARS documentation is available at: paircars.readthedocs.io
MeerSOLAR is distributed on PyPI. To use it:
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Create conda environment with python 3.10
conda create -n paircars_env python=3.10 conda activate paircars_env -
Install P-AIRCARS in conda environment
pip install paircars -
Initiate necessary metadata
init-paircars-setup --init -
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 🎉.
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To see all running P-AIRCARS jobs
show-paircars-status --show -
To see prefect dashboard
run-mwa-mwalogger -
To see local log of any job using the
run-mwa-mwalogger --jobid <jobid> -
Output products will be saved in :
<path of output products directory>
User can download and test entire P-AIRCARS pipeline using the sample dataset available in Zenodo: https://doi.org/10.5281/zenodo.16068485. Do not use this sample dataset for any publication without permission from the developer.
P-AIRCARS is developed by Devojyoti Kansabanik (NCRA-TIFR, Pune, India and CPAESS-UCAR, Boulder, USA) and an incarnation of AIRCARS. If you use P-AIRCARS for analysing your MWA solar observations, include the following statement in your paper
This MWA solar observations are analysed using P-AIRCARS pipeline.
- P-AIRCARS software in zenodo: https://doi.org/10.5281/zenodo.16040507
This project is licensed under the MIT License.