Simulating the Large-Scale Structure of HI Intensity Maps

TL;DR

This paper presents large-scale simulations of HI intensity maps to aid in understanding the large-scale structure of the universe, focusing on non-linear effects, redshift space distortions, and estimator validation for future surveys.

Contribution

It introduces high-resolution, wide-field simulations of HI intensity maps using N-body data and a halo-to-HI mass relation, enabling detailed analysis of clustering and estimator performance.

Findings

Estimators agree with analytic predictions on large scales

Non-linear effects significantly impact small-scale clustering

Covariance approximations are valid under Gaussian assumptions

Abstract

Intensity mapping of neutral hydrogen (HI) is a promising observational probe of cosmology and large-scale structure. We present wide field simulations of HI intensity maps based on N-body simulations of a $2.6\, {\rm Gpc / h}$ box with $2048^3$ particles (particle mass $1.6 \times 10^{11}\, {\rm M_\odot / h}$). Using a conditional mass function to populate the simulated dark matter density field with halos below the mass resolution of the simulation ($10^{8}\, {\rm M_\odot / h} < M_{\rm halo} < 10^{13}\, {\rm M_\odot / h}$), we assign HI to those halos according to a phenomenological halo to HI mass relation. The simulations span a redshift range of 0.35 < z < 0.9 in redshift bins of width $\Delta z \approx 0.05$ and cover a quarter of the sky at an angular resolution of about 7'. We use the simulated intensity maps to study the impact of non-linear effects and redshift space distortions on the angular clustering of HI. Focusing on the autocorrelations of the maps, we apply and compare several estimators for the angular power spectrum and its covariance. We verify that these estimators agree with analytic predictions on large scales and study the validity of approximations based on Gaussian random fields, particularly in the context of the covariance. We discuss how our results and the simulated maps can be useful for planning and interpreting future HI intensity mapping surveys.