Exploiting Non-linear Scales in Galaxy-Galaxy Lensing and Galaxy
  Clustering: A Forecast for the Dark Energy Survey
  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 $\sim1.6$ 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.
