Emulating galaxy clustering and galaxy–galaxy lensing into the deeply non-linear 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 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 ₆₆ (r) and galaxy-matter cross-correlation ₆₌ (r) as a function of ₈, 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 0. 3 arcmin^-2). Using tangential shear and projected correlation function measurements over 0. 5 rₚ 30 \, h^-1 Mpc yields a 1. 8% constraint on the parameter combination ₈ₘ^0. 58, a factor of two better than a constraint that excludes non-linear scales (rₚ > 2 \, h^-1 Mpc, 4 \, h^-1 Mpc for ₜ, wₚ). 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 ₈ₘ^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.