HI Intensity Mapping for Clustering-Based Redshift Estimation

TL;DR

This paper demonstrates that HI intensity mapping combined with spatial cross-correlations can accurately estimate redshift distributions of optical galaxy samples, reducing the need for extensive spectroscopic follow-up.

Contribution

It introduces a novel redshift distribution estimator using HI intensity maps and validates it with simulations, accounting for real-world limitations.

Findings

High-precision redshift distribution constraints achieved

Effective calibration with simulated LSST and Euclid photometry

Robustness against foreground cleaning and resolution issues

Abstract

Precision cosmology requires accurate galaxy redshifts, but next generation optical surveys will observe unprecedented numbers of resolved galaxies, placing strain on the amount of spectroscopic follow-up required. We show how useful information can be gained on the redshift distributions of optical galaxy samples from spatial cross-correlations with intensity maps of unresolved HI (21cm) spectral line emission. We construct a redshift distribution estimator, which we test using simulations. We utilise the S3-SAX catalogue which includes HI emission information for each galaxy, which we use to construct HI intensity maps. We also make use of simulated LSST and Euclid-like photometry enabling us to apply the HI clustering calibration to realistic simulated photometric redshifts. While taking into account important limitations to HI intensity mapping such as lost k-modes from foreground cleaning and poor angular resolution due to large receiver beams, we show that excellent constraints on redshift distributions can be provided for an optical photometric sample.