Mitigating gain calibration errors from EoR observations with SKA1-Low AA*

Abstract

The observations of the redshifted 21-cm signal from neutral hydrogen are a promising probe for understanding the Cosmic Dawn and the Epoch of Reionisation (EoR). One of the primary obstacles to the statistical detection of the Cosmological signal is the presence of residual foreground arising from gain calibration errors. Previous studies have shown that gain calibration errors as small as 0.01% can lead to a biased interpretation of the observed signal power spectrum estimation, by nearly an order of magnitude. A recent study further highlights that to accurately retrieve astrophysical parameters, the threshold gain calibration error should be below 0.01%. This work investigates the impact of residual extragalactic foregrounds arising from gain calibration errors on the efficacy of foreground mitigation strategies. We use an end-to-end pipeline 21cmE2E to simulate a realistic sky model and telescope configuration within the 138�146 MHz frequency range and perform a detailed power spectrum analysis across several threshold levels of the gain calibration error. We introduce a hybrid mitigation technique that combines the foreground removal techniques, Gaussian process regression and principal component analysis, with foreground avoidance. Our results indicate that recovery of the Hi signal within 2? is possible for calibration gain error of ? 1% with minimal loss of power spectrum sensitivity over the scale range 0.05 ? k ? 0.5 Mpc-1. We find that gain calibration errors beyond this threshold lead to signal suppression on large scales due to the loss of spectral smoothness of the residual foreground. In effect, this work offers a comparative assessment of three foreground mitigation strategies, removal, avoidance, and a hybrid approach, in the context of future SKA1-Low AA*�observations. � 2026 IOP Publishing Ltd and Sissa Medialab. All rights, including for text and data mining, AI training, and similar technologies, are reserved. This article is available under the terms of the https://publishingsupport.iopscience.iop.org/iop-standard/v1.