Empirical Covariance Modeling for 21 cm Power Spectrum Estimation: A Method Demonstration and New Limits from Early Murchison Widefield Array 128-Tile Data

TL;DR

This paper introduces a data-driven method to model foreground residuals' covariance in 21 cm power spectrum estimation, demonstrating its application with MWA data to set new upper limits on the high-redshift hydrogen signal.

Contribution

It presents a novel approach to infer foreground residual covariance directly from data, improving the accuracy of 21 cm power spectrum analysis.

Findings

Set a new upper limit on the 21 cm power spectrum at z=6.8

Demonstrated the covariance inference method with real MWA data

Results are consistent with previous limits, validating the approach.

Abstract

The separation of the faint cosmological background signal from bright astrophysical foregrounds remains one of the most daunting challenges of mapping the high-redshift intergalactic medium with the redshifted 21 cm line of neutral hydrogen. Advances in mapping and modeling of diffuse and point source foregrounds have improved subtraction accuracy, but no subtraction scheme is perfect. Precisely quantifying the errors and error correlations due to missubtracted foregrounds allows for both the rigorous analysis of the 21 cm power spectrum and for the maximal isolation of the "EoR window" from foreground contamination. We present a method to infer the covariance of foreground residuals from the data itself in contrast to previous attempts at a priori modeling. We demonstrate our method by setting limits on the power spectrum using a 3 h integration from the 128-tile Murchison Widefield Array. Observing between 167 and 198 MHz, we find at 95% confidence a best limit of Delta^2(k) < 3.7 x 10^4 mK^2 at comoving scale k = 0.18 hMpc^-1 and at z = 6.8, consistent with existing limits.