Exploiting Non-linear Scales in Galaxy-Galaxy Lensing and Galaxy Clustering: A Forecast for the Dark Energy Survey

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 extend the N-body and halo occupation distribution (HOD) emulator method of arxiv:1907.06293 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 $A_{lens}$. We use this emulator to forecast cosmological constraints attainable from the GGL surface density profile $\Delta \Sigma (r_p)$ and the projected galaxy correlation function $w_{p,gg}(r_p)$ in the final (Year 6) DES data set over scales $r_p=0.3-30h^{-1}$ Mpc. For a $3\%$ prior on $A_{lens}$ we forecast precisions of $1.9\%$, $2.0\%$, and $1.9\%$ on ${\Omega }_m$, ${\sigma }_8$, and $S_8\equiv {\sigma }_8{\Omega }_m^{0.5}$, marginalized over all halo occupation distribution (HOD) parameters as well as $A_{lens}$ and a point-mass contribution to $\Delta \Sigma$. Adding scales $r_p=0.3-3h^{-1}$ Mpc improves the $S_8$ precision by a factor of $\sim 1.6$ relative to a large scale ($3.0-30.0h^{-1}$ Mpc) analysis, equivalent to increasing the survey area by a factor of $\sim 2.6$. Sharpening the $A_{lens}$ prior to $1\%$ further improves the $S_8$ precision by a factor of $1.7$ (to $1.1\%$), and it amplifies the gain from including non-linear scales. Our emulator achieves percent-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.

arXiv comment17 pages, 7 figures, to be submitted to MNRAS

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