A Compressed Sensing Faraday Depth Reconstruction Framework for the MeerKAT MIGHTEE-POL Survey

TL;DR

This paper introduces a new compressed sensing framework for reconstructing Faraday depth signals from noisy, incomplete radio spectro-polarimetric data, demonstrated on MeerKAT MIGHTEE survey data.

Contribution

It presents a scalable, systematic compressed sensing approach specifically designed for Faraday depth reconstruction in radio astronomy.

Findings

Effective reconstruction of Faraday depth signals from noisy data

Application to MeerKAT MIGHTEE survey data shows promising results

Addresses key challenges in spectro-polarimetric data analysis

Abstract

In this work we present a novel compute framework for reconstructing Faraday depth signals from noisy and incomplete spectro-polarimetric radio datasets. This framework is based on a compressed-sensing approach that addresses a number of outstanding issues in Faraday depth reconstruction in a systematic and scaleable manner. We apply this framework to early-release data from the MeerKAT MIGHTEE polarisation survey.