Foreground modelling via Gaussian process regression: An application to HERA data
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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
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1365-2966