Synthetic data products for future H i galaxy surveys: a tool for characterizing source confusion in spectral line stacking experiments

Abstract

Much of our current understanding of neutral, atomic gas in galaxies comes from radio observations of the nearby Universe. Until the next generation of instruments allow us to push to much higher redshifts, we must rely mostly upon theoretical models of galaxy formation to provide us with key insights into the likely cosmic evolution of HI in the Universe, and its links to molecular clouds and star formation. In this work, we present a new set of methods to convert mock galaxy catalogues into synthetic data cubes containing model galaxies with realistic spatial and spectral HI distributions over large cosmological volumes. Such synthetic data products can be used to guide observing and data handling/analysis strategies for forthcoming HI galaxy surveys. As a demonstration of the potential use of our simulated products we use them to conduct several mock HI stacking experiments for both low and high-redshift galaxy samples. The stacked spectra can be accurately decomposed into contributions from target and non-target galaxies, revealing in all co-added spectra large fractions of contaminant mass due to source confusion. Our results are consistent with similar estimates extrapolated from z=0 observational data. The amount of confused mass in a stacked spectrum grows almost linearly with the size of the observational beam, suggesting potential over-estimates of Omega_HI by some recent HI stacking experiments. Our simulations will allow the study of subtle redshift-dependent effects in future stacking analyses.