Stacking Redshifted 21cm Images of HII Regions Around High Redshift Galaxies as a Probe of Early Reionization

TL;DR

This study explores the potential of stacking redshifted 21cm images around bright high-redshift galaxies to detect early ionized regions during reionization, using simulations and mock observations with the SKA.

Contribution

It demonstrates that stacking can detect average ionized regions at high redshift and assesses the impact of foreground contamination on detection significance.

Findings

A 5σ detection is possible with perfect foreground removal using 30 images.

Foreground contamination significantly hampers detection, but partial subtraction improves results.

Reducing foreground Fourier space by 50-80% enhances detection confidence to above 3σ and 5σ.

Abstract

A number of current and future experiments aim to detect the reionization of neutral hydrogen by the first stars and galaxies in the Universe via the redshifted 21cm line. Using the \textsc{BlueTides} simulation, we investigate the measurement of an \textit{average} ionised region towards the beginning of reionization by stacking redshifted 21cm images around optically identified bright galaxies using mock observations. We find that with an SKA 1000 hour observation, assuming perfect foreground subtraction, a $5\sigma$ detection of a stacked HII region can be made with 30 images around some of the brightest galaxies in \textsc{bluetides} (brighter than $M_{UV} < -22.75$) at $z=9$ (corresponding to a neutral fraction of 90.1 \% in our model). We present simulated relationships between the UV magnitude of galaxies, the sizes of the ionised regions they reside in, and the shape of the stacked profiles. These mock observations can also distinguish between scenarios where the IGM is in net emission or absorption of 21cm photons. Once 21cm foreground contamination is included, we find that even with up to 200 images around these rare, bright galaxies, only a tentative $> 1\sigma$ detection will be possible. However, partial foreground subtraction substantially improves signal-to-noise. For example, we predict that reducing the area of Fourier space dominated by foregrounds by 50 (80) percent will allow $> 3\sigma$ ($> 5\sigma$) detections of ionised regions at $z=9$.