P-AIRCARS Documentation

P-AIRCARS is an automated calibration and imaging pipeline designed for solar radio observations using 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.

Introduction

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

  • Pipeline workflow is managed by prefect leveraging Dask for scalable parallel processing

  • Providing hooks for integration with contextual data from other wavelegths for enhanced solar analysis

Features of P-AIRCARS

P-AIRCARS serves as a reference pipeline for science-ready processing of P-AIRCARS solar observations. It is designed to:

  • Calibrate and image non-trivial solar observations

  • Enable reproducible science through consistent and documented data reduction steps

  • Designed to use on personal computer, single-node workstations, as well as in high-performance computing multi-node cluster

  • A free-tier cloud-based remote logger to monitor pipeline over the internet

Software environment

P-AIRCARS is tested on operating systems, Ubunut 22, Ubunut 24, and CentOS7 under Python 3.10 environment. Using P-AIRCARS in other operating systems and python version does not gurantee successful run and limited support for debugging is available. User may look at Containersed Use section in those scenarios.

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.

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