Removing systematics-induced 21-cm foreground residuals by cross-correlating filtered data
Haochen Wang, Juan Mena-Parra, Tianyue Chen, and Kiyoshi Masui

TL;DR
This paper introduces a robust method combining linear and non-linear techniques to remove systematic-induced foreground residuals in 21-cm cosmology data, significantly improving signal recovery in simulations.
Contribution
It proposes a novel cross-correlation-based correction method that effectively reduces systematics-induced foreground residuals in 21-cm observations.
Findings
Removes foreground leakage by 1-2 orders of magnitude in simulations.
Eases telescope calibration requirements for future 21-cm experiments.
Demonstrates robustness against complex gain errors.
Abstract
Observations of the redshifted 21-cm signal emitted by neutral hydrogen represent a promising probe of large-scale structure in the universe. However, cosmological 21-cm signal is challenging to observe due to astrophysical foregrounds which are several orders of magnitude brighter. Traditional linear foreground removal methods can optimally remove foregrounds for a known telescope response but are sensitive to telescope systematic errors such as antenna gain and delay errors, leaving foreground contamination in the recovered signal. Non-linear methods such as principal component analysis, on the other hand, have been used successfully for foreground removal, but they lead to signal loss that is difficult to characterize and requires careful analysis. In this paper, we present a systematics-robust foreground removal technique which combines both linear and non-linear methods. We first…
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