Identifying Ionized Regions in Noisy Redshifted 21 cm Data Sets
Matthew Malloy, Adam Lidz

TL;DR
This paper demonstrates that upcoming noisy 21 cm data sets can be used to directly identify ionized regions during reionization using matched filtering, enabling new insights despite sensitivity limitations.
Contribution
It introduces a method to detect ionized regions in noisy 21 cm data using matched filters, informing future survey design and analysis strategies.
Findings
MWA can identify ionized regions despite thermal noise
Up to 150 ionized regions detectable in a 6 MHz survey volume
Size of ionized regions can be roughly determined
Abstract
One of the most promising approaches for studying reionization is to use the redshifted 21 cm line. Early generations of redshifted 21 cm surveys will not, however, have the sensitivity to make detailed maps of the reionization process, and will instead focus on statistical measurements. Here we show that it may nonetheless be possible to {\em directly identify ionized regions} in upcoming data sets by applying suitable filters to the noisy data. The locations of prominent minima in the filtered data correspond well with the positions of ionized regions. In particular, we corrupt semi-numeric simulations of the redshifted 21 cm signal during reionization with thermal noise at the level expected for a 500 antenna tile version of the Murchison Widefield Array (MWA), and mimic the degrading effects of foreground cleaning. Using a matched filter technique, we find that the MWA should be…
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