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

• Published in: arXiv.org
• Main Authors: Storey-Fisher, Kate, Tinker, Jeremy, Zhai, Zhongxu, DeRose, Joseph, Wechsler, Risa H, Banerjee, Arka
• Format: Paper Journal Article
• Language: English
• Published: Ithaca Cornell University Library, arXiv.org 12.03.2024
• Subjects: Assembly; Bias; Clustering; Constraining; Correlation; Density; Emulators; Galaxies; Gaussian process; Mathematical models; Parameter sensitivity; Physics - Astrophysics of Galaxies; Physics - Cosmology and Nongalactic Astrophysics; Physics - Instrumentation and Methods for Astrophysics; Quadrupoles; Red shift
• ISSN: 2331-8422
• DOI: 10.48550/arxiv.2210.03203

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.