Cosmology with a SKA HI intensity mapping survey

TL;DR

This paper explores the potential of SKA1 HI intensity mapping to map the universe's large-scale structure across various redshifts, enabling precise cosmological measurements and tests of fundamental physics.

Contribution

It assesses SKA1's capability to produce HI intensity maps over a broad frequency range and sky area, analyzing survey design, foregrounds, and autocorrelation use for cosmological constraints.

Findings

SKA1 can effectively map large-scale structures across a wide redshift range.

HI intensity mapping can constrain dark energy, gravity modifications, and primordial non-Gaussianity.

Foregrounds and instrumental parameters significantly impact measurement precision.

Abstract

HI intensity mapping (IM) is a novel technique capable of mapping the large-scale structure of the Universe in three dimensions and delivering exquisite constraints on cosmology, by using HI as a biased tracer of the dark matter density field. This is achieved by measuring the intensity of the redshifted 21cm line over the sky in a range of redshifts without the requirement to resolve individual galaxies. In this chapter, we investigate the potential of SKA1 to deliver HI intensity maps over a broad range of frequencies and a substantial fraction of the sky. By pinning down the baryon acoustic oscillation and redshift space distortion features in the matter power spectrum -- thus determining the expansion and growth history of the Universe -- these surveys can provide powerful tests of dark energy models and modifications to General Relativity. They can also be used to probe physics on extremely large scales, where precise measurements of spatial curvature and primordial non-Gaussianity can be used to test inflation; on small scales, by measuring the sum of neutrino masses; and at high redshifts where non-standard evolution models can be probed. We discuss the impact of foregrounds as well as various instrumental and survey design parameters on the achievable constraints. In particular we analyse the feasibility of using the SKA1 autocorrelations to probe the large-scale signal.