Cosmology with galaxy cluster weak lensing: statistical limits and experimental design

TL;DR

This paper forecasts how well upcoming weak lensing surveys can measure matter clustering using galaxy clusters, emphasizing the importance of controlling systematics and the potential of targeted observations.

Contribution

It introduces a novel approach combining cluster counts and weak lensing profiles, providing forecasts and analytic tools for future survey constraints on sigma_8.

Findings

Forecasted sigma_8 constraints: 0.10% to 0.26% for upcoming surveys.

A one-month Roman survey could achieve 0.5% precision on sigma_8 at z=0.7.

Accurate mass-observable relation knowledge is crucial for maximizing constraints.

Abstract

We forecast constraints on the amplitude of matter clustering sigma_8(z) achievable with the combination of cluster weak lensing and number counts, in current and next-generation weak lensing surveys. We advocate an approach, analogous to galaxy-galaxy lensing, in which the observables in each redshift bin are the mean number counts and the mean weak lensing profile of clusters above a mass proxy threshold. The primary astrophysical nuisance parameter is the logarithmic scatter between the mass proxy and true mass near the threshold. For surveys similar to the Dark Energy Survey (DES), the Roman Space Telescope High Latitude Survey (HLS), and the Rubin Observatory Legacy Survey of Space and Time (LSST), we forecast aggregate precision on sigma_8 of 0.26%, 0.24%, and 0.10%, respectively, if the mass-observable scatter has an external prior better than 0.01. These constraints would be degraded by about 20% for a 0.05 prior on scatter in the case of DES or HLS and for a 0.016 prior for LSST. A one-month observing program with Roman Space Telescope targeting approximately 2500 massive clusters could achieve a 0.5% constraint on sigma_8(z=0.7) on its own, or a ~0.33% constraint in combination with the HLS. Realizing the constraining power of clusters requires accurate knowledge of the mass-observable relation and stringent control of systematics. We provide analytic approximations to our numerical results that allow easy scaling to other survey assumptions or other methods of cluster mass estimation.