{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/the-aemulus-project-vi-emulation-of-beyond","title":"The Aemulus Project VI: Emulation of beyond-standard galaxy clustering statistics to improve cosmological constraints","arxiv_id":"2210.03203","date":"2022-10-06","proceeding":null,"authors":["Kate Storey-Fisher","Jeremy Tinker","Zhongxu Zhai","Joseph DeRose","Risa H. Wechsler","Arka Banerjee"],"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.","url_abs":"https://arxiv.org/abs/2210.03203v2","url_pdf":"https://arxiv.org/pdf/2210.03203v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"the-aemulus-project-vi-emulation-of-beyond","repo_url":"https://github.com/kstoreyf/aemulator","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}