The Aemulus Project III: Emulation of the Galaxy Correlation Function

TL;DR

This paper introduces a galaxy clustering emulator based on AEMULUS simulations that achieves high precision and improves constraints on cosmological parameters by analyzing small-scale clustering data.

Contribution

The paper presents a new emulator for galaxy clustering that incorporates galaxy bias and velocity bias, enabling more precise cosmological parameter estimation from small-scale data.

Findings

Achieves ~1% precision in galaxy clustering modeling at 0.1<r<10 h^{-1} Mpc.

Tighter constraints on fσ_8 compared to traditional perturbation theory methods.

Breaks degeneracy between f and σ_8, providing 9% constraint on f alone.

Abstract

Using the N-body simulations of the AEMULUS Project, we construct an emulator for the non-linear clustering of galaxies in real and redshift space. We construct our model of galaxy bias using the halo occupation framework, accounting for possible velocity bias. The model includes 15 parameters, including both cosmological and galaxy bias parameters. We demonstrate that our emulator achieves ~ 1% precision at the scales of interest, 0.1<r<10 h^{-1} Mpc, and recovers the true cosmology when tested against independent simulations. Our primary parameters of interest are related to the growth rate of structure, f, and its degenerate combination fsigma_8. Using this emulator, we show that the constraining power on these parameters monotonically increases as smaller scales are included in the analysis, all the way down to 0.1 h^{-1} Mpc. For a BOSS-like survey, the constraints on fsigma_8 from r<30 h^{-1} Mpc scales alone are more than a factor of two tighter than those from the fiducial BOSS analysis of redshift-space clustering using perturbation theory at larger scales. The combination of real- and redshift-space clustering allows us to break the degeneracy between f and sigma_8, yielding a 9% constraint on f alone for a BOSS-like analysis. The current AEMULUS simulations limit this model to surveys of massive galaxies. Future simulations will allow this framework to be extended to all galaxy target types, including emission-line galaxies.