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Foreground modelling via Gaussian process regression: An application to HERA data

Accepted version
Peer-reviewed

Type

Article

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Authors

Ghosh, A 
Mertens, F 
Bernardi, G 
Santos, MG 
Kern, NS 

Abstract

The key challenge in the observation of the redshifted 21-cm signal from cosmic reionization is its separation from the much brighter foreground emission. Such separation relies on the different spectral properties of the two components, although, in real life, the foreground intrinsic spectrum is often corrupted by the instrumental response, inducing systematic effects that can further jeopardize the measurement of the 21-cm signal. In this paper, we use Gaussian Process Regression to model both foreground emission and instrumental systematics in ∼2 hours of data from the Hydrogen Epoch of Reionization Array. We find that a simple co-variance model with three components matches the data well, giving a residual power spectrum with white noise properties. These consist of an "intrinsic" and instrumentally corrupted component with a coherence-scale of 20 MHz and 2.4 MHz respectively (dominating the line of sight power spectrum over scales k≤0.2 h cMpc−1) and a baseline dependent periodic signal with a period of ∼1 MHz (dominating over k∼0.4−0.8h cMpc−1) which should be distinguishable from the 21-cm EoR signal whose typical coherence-scales is ∼0.8 MHz.

Description

Keywords

instrumentation: interferometers, methods: statistical, dark ages, reionization, first stars, diffuse radiation, large-scale structure of Universe, cosmology: observations

Journal Title

Monthly Notices of the Royal Astronomical Society

Conference Name

Journal ISSN

0035-8711
1365-2966

Volume Title

495

Publisher

Oxford University Press (OUP)

Rights

All rights reserved