Statistical selection of high-redshift, neutral-hydrogen-rich, lensed galaxies with the Square Kilometre Array
Year: 2025
Type: article
Abstract: ABSTRACT Deep wide spectral line surveys with the Square Kilometre Array (SKA) will expand the cosmic frontiers of neutral atomic hydrogen (H i) in galaxies. However, at cosmologically significant redshifts ($z \gtrsim 0.5$), detections will typically be spatially unresolved and limited to the highest mass systems. Gravitational lensing could potentially alleviate these limitations, enabling lower mass systems to be studied at higher redshift and spatially resolved dynamical studies of some H i discs. Additionally, lensed H i systems would select foreground dark matter haloes using a different, more extended baryonic tracer compared to other lens surveys. This may result in a wider selected range of foreground dark matter halo properties, such as the concentration parameter. This paper uses the distortion of the observed H i mass function produced by strong gravitational lensing to find a flux density criterion for selecting lensed H i sources in future SKA-Mid spectral line surveys. This selection approach could yield lensed H i source densities in the range of ${\sim} 0.1$–10 galaxies per square degree out to a redshift of $z \simeq 3$ covered by SKA-MID Band 1. Although the sample sizes are modest, even with the proposed SKA-Mid surveys, the selection approach is straightforward and should have a 50 per cent efficiency without any additional information, such as low-impact-factor or lower redshift massive galaxies. The efficiency of selecting high-redshift, neutral-hydrogen-rich, lensed galaxies should then be greatly enhanced by using SKA-MID data in concert with the Vera C. Rubin Large Survey of Space and Time.
Authors: Charissa B Button, Roger P Deane
Institutions: University of Pretoria, University of the Witwatersrand
Language: English
Subfield: Astronomy and Astrophysics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $3,046
Awards: G2869686227, G8884770708
OpenAlex ID: W4407398294