Wavelets and sparsity for Faraday tomography
arXiv:2112.01444 · doi:10.1093/pasj/psac052
Abstract
Faraday tomography through broadband polarimetry can provide crucial information on magnetized astronomical objects, such as quasars, galaxies, or galaxy clusters. However, the limited wavelength coverage of the instruments requires that we solve an ill-posed inverse problem when we want to obtain the Faraday dispersion function (FDF), a tomographic distribution of the magnetoionic media along the line of sight. This paper explores the use of wavelet transforms and the sparsity of the transformed FDFs in the form of wavelet shrinkage (WS) for finding better solutions to the inverse problem. We recently proposed the Constraining and Restoring iterative Algorithm for Faraday Tomography (CRAFT; Cooray et al. 2021), a new flexible algorithm that showed significant improvements over the popular methods such as Rotation Measure Synthesis. In this work, we introduce CRAFT+WS, a new version of CRAFT incorporating the ideas of wavelets and sparsity. CRAFT+WS exhibit significant improvements over the original CRAFT when tested for a complex FDF of realistic Galactic model. Reconstructions of FDFs demonstrate super-resolution in Faraday depth, uncovering previously unseen Faraday complexities in observations. The proposed approach will be necessary for effective cosmic magnetism studies using the Square Kilometre Array and its precursors.
10 Pages, 3 Figures, Submitted to PASJ. Code will be made available upon publication
References in corpus (9)
- Radio observational constraints on Galactic 3D-emission models
- The Australian Square Kilometre Array Pathfinder: Performance of the Boolardy Engineering Test Array
- Cosmic Magnetism in Centimeter and Meter Wavelength Radio Astronomy
- Exploring the Intergalactic Magnetic Field by Means of Faraday Tomography
- Faraday dispersion functions of galaxies
- An Iterative Reconstruction Algorithm for Faraday Tomography
- Gaussian Process Modelling for Improved Resolution in Faraday Depth Reconstruction
- Modified Papoulis-Gerchberg algorithm for sparse signal recovery
- A Method for Unmasking Incomplete Astronomical Signals: Application to CO Multi-line Imaging of Nearby Galaxies Project