Emulating galaxy clustering and galaxy-galaxy lensing into the deeply nonlinear regime: methodology, information, and forecasts
Abstract
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 gg(r) and galaxy-matter cross-correlation gm(r) as a function of σ8, 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 σ8m0.58, a factor of two better than a constraint that excludes non-linear scales (rp > 2 \, h-1 Mpc, 4 \, h-1 Mpc for γt,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 σ8m0.58 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.
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