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

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    staa1331.pdf (15.63Mb)
    Date
    2020
    Author
    Ghosh, Abhik
    Mertens, Florent
    Bernardi, Gianni
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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 ∼2 h of data from the Hydrogen Epoch of Reionization Array.
    URI
    https://doi.org/10.1093/mnras/staa1331
    http://hdl.handle.net/10566/5919
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    • Research Articles (Physics)

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