Abstract

Image formation for radio interferometers such as the Square Kilometre Array (SKA) is an inverse problem, subject to a number of complications, both intrinsic to the measurement process and influenced by external factors. Beyond standard image formation, the tomographic reconstruction of Faraday depth structure from incomplete spectral polarization measurements with radio interferometers is an under-constrained problem requiring additional regularisation. In this talk I will describe how Faraday depth tomography can be used to reconstruct magnetic structures along the telescope’s line of sight and introduce a novel object-oriented compressed sensing framework to reconstruct these data. Unlike previous compressed sensing applications in this field, 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. Furthermore, the framework is scalable to large data volumes such as those that will be produced by the SKA telescope and its precursors. I will also introduce our methodology for identifying an optimal basis function for reconstruction of these data, using an approach that can be applied to datasets from other telescopes and over different frequency ranges.