The Aemulus Project. VI. Emulation of Beyond-standard Galaxy Clustering Statistics to Improve Cosmological Constraints

Abstract

There is untapped cosmological information in galaxy redshift surveys in the nonlinear 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 Mpc) in order to constrain cosmological and galaxy bias parameters. In addition to standard statistics—the projected correlation function w _p ( r _p ), the redshift-space monopole of the correlation function ξ _0 ( s ), and the quadrupole ξ _2 ( s )—we emulate statistics that include information about the local environment, namely the underdensity probability function P _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 _U ( s ) and M ( s ) improves the precision of our constraints on Ω _m by 27%, σ _8 by 19%, and the growth of structure parameter, f σ _8 , by 12% compared to standard statistics. We additionally find that scales below ∼6 h ^−1 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.

Keywords

• Large-scale structure of the universe
• Cosmological parameters
• Computational methods
• Astrostatistics