Robust Foregrounds Removal for 21-cm Experiments

TL;DR

This paper introduces a novel Gaussian Process Regression method and a maximum likelihood imaging framework to accurately separate the weak 21-cm cosmological signal from dominant foregrounds and instrumental effects in Epoch of Reionization experiments.

Contribution

It presents a new foreground removal technique using GPR and an advanced imaging method that directly solves the interferometric equation on the sphere, improving signal recovery.

Findings

Effective separation of 21-cm signal from foregrounds.

Elimination of chromatic effects in the power spectrum.

Enhanced accuracy in Epoch of Reionization measurements.

Abstract

Direct detection of the Epoch of Reionization via the redshifted 21-cm line will have unprecedented implications on the study of structure formation in the early Universe. To fulfill this promise current and future 21-cm experiments will need to detect the weak 21-cm signal over foregrounds several order of magnitude greater. This requires accurate modeling of the galactic and extragalactic emission and of its contaminants due to instrument chromaticity, ionosphere and imperfect calibration. To solve for this complex modeling, we propose a new method based on Gaussian Process Regression (GPR) which is able to cleanly separate the cosmological signal from most of the foregrounds contaminants. We also propose a new imaging method based on a maximum likelihood framework which solves for the interferometric equation directly on the sphere. Using this method, chromatic effects causing the so-called "wedge" are effectively eliminated (i.e. deconvolved) in the cylindrical ($k_{\perp}, k_{\parallel}$) power spectrum.