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Title: 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 theAemulussuite of cosmologicalN-body simulations to construct Gaussian process emulators of galaxy clustering statistics at small scales (0.1–50h−1Mpc) in order to constrain cosmological and galaxy bias parameters. In addition to standard statistics—the projected correlation functionwp(rp), the redshift-space monopole of the correlation functionξ0(s), and the quadrupoleξ2(s)—we emulate statistics that include information about the local environment, namely the underdensity probability functionPU(s) and the density-marked correlation functionM(s). This extends the model ofAemulusIII 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: includingPU(s) andM(s) improves the precision of our constraints on Ωmby 27%,σ8by 19%, and the growth of structure parameter,fσ8, by 12% compared to standard statistics. We additionally find that scales below ∼6h−1Mpc 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.  more » « less
Award ID(s):
2009291
PAR ID:
10510910
Author(s) / Creator(s):
; ; ; ; ;
Publisher / Repository:
Astrophysical Journal
Date Published:
Journal Name:
The Astrophysical Journal
Volume:
961
Issue:
2
ISSN:
0004-637X
Page Range / eLocation ID:
208
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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