TL;DR
CS-ROMER is a new compressed sensing framework that accurately reconstructs Faraday depth structures from irregularly sampled spectro-polarization radio data, improving analysis of cosmic magnetic fields.
Contribution
This work introduces cs-romer, a novel object-oriented compressed sensing framework capable of handling irregular data sampling and multiple regularizations for Faraday depth reconstruction.
Findings
Delta basis function yields optimal reconstruction for VLA L-band data.
Successfully reconstructed Faraday depth of galaxies in Abell 1314.
Reconstructed Faraday rotation dominated by local environments of galaxies.
Abstract
The reconstruction of Faraday depth structure from incomplete spectral polarization radio measurements using the RM Synthesis technique is an under-constrained problem requiring additional regularisation. In this paper we present cs-romer: a novel object-oriented compressed sensing framework to reconstruct Faraday depth signals from spectro-polarization radio data. Unlike previous compressed sensing applications, this framework is designed to work directly with data that are irregularly sampled in wavelength-squared space and to incorporate multiple forms of compressed sensing regularisation. We demonstrate the framework using simulated data for the VLA telescope under a variety of observing conditions, and we introduce a methodology for identifying the optimal basis function for reconstruction of these data, using an approach that can also be applied to datasets from other telescopes…
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