The Aemulus Project VI: Emulation of beyond-standard galaxy clustering statistics to improve cosmological constraints

TL;DR

This paper develops Gaussian process emulators for small-scale galaxy clustering statistics, including environment-sensitive measures, to enhance cosmological parameter constraints from galaxy surveys.

Contribution

It introduces emulators for beyond-standard clustering statistics, incorporating environment information, to improve cosmological constraints and galaxy-halo connection understanding.

Findings

Including environment-sensitive statistics improves parameter constraints by up to 27%.

Small scales below 6 h^{-1} Mpc contain as much information as larger scales.

Environment-dependent models help constrain galaxy-halo connection and cosmology.

Abstract

There is untapped cosmological information in galaxy redshift surveys in the non-linear regime. In this work, we use the AEMULUS suite of cosmological $N$-body simulations to construct Gaussian process emulators of galaxy clustering statistics at small scales ($0.1-50 \: h^{-1}\,\mathrm{Mpc}$) in order to constrain cosmological and galaxy bias parameters. In addition to standard statistics -- the projected correlation function $w_\mathrm{p}(r_\mathrm{p})$, the redshift-space monopole of the correlation function $\xi_0(s)$, and the quadrupole $\xi_2(s)$ -- we emulate statistics that include information about the local environment, namely the underdensity probability function $P_\mathrm{U}(s)$ and the density-marked correlation function $M(s)$. This extends the model of AEMULUS III for redshift-space distortions by including new statistics sensitive to galaxy assembly bias. In recovery tests, we find that the beyond-standard statistics significantly increase the constraining power on cosmological parameters of interest: including $P_\mathrm{U}(s)$ and $M(s)$ improves the precision of our constraints on $\Omega_m$ by 27%, $\sigma_8$ by 19%, and the growth of structure parameter, $f \sigma_8$, by 12% compared to standard statistics. We additionally find that scales below $\sim6 \: h^{-1}\,\mathrm{Mpc}$ contain as much information as larger scales. The density-sensitive statistics also contribute to constraining halo occupation distribution parameters and a flexible environment-dependent assembly bias model, which is important for extracting the small-scale cosmological information as well as understanding the galaxy-halo connection. This analysis demonstrates the potential of emulating beyond-standard clustering statistics at small scales to constrain the growth of structure as a test of cosmic acceleration.