http://arxiv.org/abs/2212.07415
In a sky-averaged 21-cm signal experiment aiming to measure the sky-averaged brightness temperature of neutral hydrogen at high redshifts, the uncertainty on the extracted signal depends mainly on the covariance between the foreground and 21-cm signal models. In this paper, we construct these models using the modes of variation obtained from the Singular Value Decomposition of a set of simulated foreground and 21-cm signals. We present a strategy to reduce this overlap between the 21-cm and foreground modes by simultaneously fitting the spectra from multiple different antennas, which can be used in combination with the method of utilizing the time dependence of foregrounds while fitting multiple drift scan spectra. To demonstrate this idea, we consider two different foreground models (i) a simple foreground model, where we assume a constant spectral index over the sky, and (ii) a more realistic foreground model, where we assume a spatial variation of the spectral index. For the simple foreground model, with just a single antenna design, we are able to extract the signal with good accuracy if we simultaneously fit the data from multiple time slices. The 21-cm signal extraction is further improved when we simultaneously fit the data from different antennas as well. The impact of including different antennas in the fitting becomes prominent while using the more realistic mock observations generated from a detailed foreground model. We find that even if we fit multiple time slices, the recovered signal is biased and inaccurate if only a single antenna type is used. However, simultaneously fitting the data from multiple antenna types reduces the bias and the uncertainty by a factor of 2-3 on the extracted 21-cm signal. Although our analysis is based on the three antenna designs considered in the REACH experiment, these results can be utilized for any global 21-cm signal experiment.
A. Saxena, P. Meerburg, E. Acedo, et. al.
Thu, 15 Dec 22
32/75
Comments: 11 pages, 13 figures. Submitted to MNRAS. Comments are welcome
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