The cosmology dependence of galaxy clustering and lensing from a hybrid $N$-body-perturbation theory model

TL;DR

This paper presents a hybrid model combining N-body simulations and analytic bias expansion to accurately emulate galaxy clustering and lensing statistics across different cosmologies, aiding future survey analyses.

Contribution

The authors develop a fast, accurate emulator for nonlinear galaxy clustering and lensing that incorporates cosmology dependence and complex tracer effects, improving analysis capabilities.

Findings

Emulation accuracy is sub-percent at relevant scales for upcoming surveys.

The emulator reliably fits complex tracer samples including assembly bias.

It enables unbiased cosmological inference from simulated joint clustering and lensing data.

Abstract

We implement a model for the two-point statistics of biased tracers that combines dark matter dynamics from $N$-body simulations with an analytic Lagrangian bias expansion. Using Aemulus, a suite of $N$-body simulations built for emulation of cosmological observables, we emulate the cosmology dependence of these nonlinear spectra from redshifts $z = 0$ to $z=2$. We quantify the accuracy of our emulation procedure, which is sub-per cent at $k=1\, h {\rm Mpc}^{-1}$ for the redshifts probed by upcoming surveys and improves at higher redshifts. We demonstrate its ability to describe the statistics of complex tracer samples, including those with assembly bias and baryonic effects, reliably fitting the clustering and lensing statistics of such samples at redshift $z\simeq 0.4$ to scales of $k_{\rm max} \approx 0.6\, h\mathrm{Mpc}^{-1}$. We show that the emulator can be used for unbiased cosmological parameter inference in simulated joint clustering and galaxy--galaxy lensing analyses with data drawn from an independent $N$-body simulation. These results indicate that our emulator is a promising tool that can be readily applied to the analysis of current and upcoming datasets from galaxy surveys.