Emulating galaxy clustering and galaxy-galaxy lensing into the deeply nonlinear regime: methodology, information, and forecasts
The combination of galaxy-galaxy lensing (GGL) with galaxy clustering is one of the most promising routes to determining the amplitude of matter clustering at low redshifts. We show that extending clustering+GGL analyses from the linear regime down to $\sim 0.5 \, h^{-1}$ Mpc scales increases their constraining power considerably, even after marginalizing over a flexible model of non-linear galaxy bias. Using a grid of cosmological N-body simulations, we construct a Taylor-expansion emulator that predicts the galaxy autocorrelation $ξ_{\text{gg}}(r)$ and galaxy-matter cross-correlation $ξ_{\text{gm}}(r)$ as a function of $σ_8$, $Ω_m$, and halo occupation distribution (HOD) parameters, which are allowed to vary with large scale environment to represent possible effects of galaxy assembly bias. We present forecasts for a fiducial case that corresponds to BOSS LOWZ galaxy clustering and SDSS-depth weak lensing (effective source density $\sim 0.3$ arcmin$^{-2}$). Using tangential shear and projected correlation function measurements over $0.5 \leq r_p \leq 30 \, h^{-1}$ Mpc yields a 1.8% constraint on the parameter combination $σ_8Ω_m^{0.58}$, a factor of two better than a constraint that excludes non-linear scales ($r_p > 2 \, h^{-1}$ Mpc, $4 \, h^{-1}$ Mpc for $γ_t,w_p$). Much of this improvement comes from the non-linear clustering information, which breaks degeneracies among HOD parameters that would otherwise degrade the inference of matter clustering from GGL. Increasing the effective source density to $3$ arcmin$^{-2}$ sharpens the constraint on $σ_8Ω_m^{0.58}$ by a further factor of two. With robust modeling into the non-linear regime, low-redshift measurements of matter clustering at the 1-percent level with clustering+GGL alone are well within reach of current data sets such as those provided by the Dark Energy Survey.