Document Type
Article
Publication Date
3-2022
Copyright Statement
This article has been accepted for publication in Monthly Notices of the Royal Astronomical Society ©: 2022 The Authors. Published by Oxford University Press on behalf of the Royal Astronomical Society. All rights reserved. https://doi.org/10.1093/mnras/stab3793
Publication Information
Salcedo, Andrés N.; Weinberg, David H.; Wu, Hao-Yi; and Wibking, Benjamin D.. (2022). "Exploiting Non-Linear Scales in Galaxy–Galaxy Lensing and Galaxy Clustering: A Forecast for the Dark Energy Survey". Monthly Notices of the Royal Astronomical Society, 510(4), 5376-5391. https://doi.org/10.1093/mnras/stab3793
Comments
Abstract
The combination of galaxy–galaxy lensing (GGL) and galaxy clustering is a powerful probe of low-redshift matter clustering, especially if it is extended to the non-linear regime. To this end, we use an N-body and halo occupation distribution (HOD) emulator method to model the redMaGiC sample of colour-selected passive galaxies in the Dark Energy Survey (DES), adding parameters that describe central galaxy incompleteness, galaxy assembly bias, and a scale-independent multiplicative lensing bias Alens. We use this emulator to forecast cosmological constraints attainable from the GGL surface density profile ΔΣ(rp) and the projected galaxy correlation function wp, gg(rp) in the final (Year 6) DES data set over scales rp = 0.3−30.0 h−1 Mpc. For a 3 per cent prior on Alens we forecast precisions of 1.9 per cent, 2.0 per cent, and 1.9 per cent on Ωm, σ8, and
, marginalized over all halo occupation distribution (HOD) parameters as well as Alens. Adding scales rp = 0.3−30.0 h−1 Mpc improves the S8 precision by a factor of ∼1.6 relative to a large scale (3.0−30.0 h−1 Mpc) analysis, equivalent to increasing the survey area by a factor of ∼2.6. Sharpening the Alens prior to 1 per cent further improves the S8 precision to 1.1 per cent, and it amplifies the gain from including non-linear scales. Our emulator achieves per cent-level accuracy similar to the projected DES statistical uncertainties, demonstrating the feasibility of a fully non-linear analysis. Obtaining precise parameter constraints from multiple galaxy types and from measurements that span linear and non-linear clustering offers many opportunities for internal cross-checks, which can diagnose systematics and demonstrate the robustness of cosmological results.