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The Aemulus Project VI: Emulation of beyond-standard galaxy clustering statistics to improve cosmological constraints
Kate Storey-Fisher, Jeremy Tinker, Zhongxu Zhai, Joseph DeRose, Risa H. Wechsler, Arka Banerjee
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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 Mpc) in order to constrain cosmological and galaxy bias parameters. In addition to standard statistics -- the projected correlation function wₚ(rₚ), the redshift-space monopole of the correlation function ξ₀(s), and the quadrupole ξ₂(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 Ωₘ by 27%, σ₈ by 19%, and the growth of structure parameter, f σ₈, 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.
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