{"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/fremu-power-spectrum-emulator-for-f-r-gravity","title":"FREmu: Power Spectrum Emulator for $f(R)$ Gravity","arxiv_id":"2405.05840","date":"2024-05-09","proceeding":null,"authors":["Jiachen Bai","Junqing Xia"],"abstract":"To investigate gravity in the non-linear regime of cosmic structure using measurements from Stage-IV surveys, it is imperative to accurately compute large-scale structure observables, such as non-linear matter power spectra, for gravity models that extend beyond general relativity. However, the theoretical predictions of non-linear observables are typically derived from N-body simulations, which demand substantial computational resources. In this study, we introduce a novel public emulator, termed FREmu, designed to provide rapid and precise forecasts of non-linear power spectra specifically for the Hu-Sawicki $f(R)$ gravity model across scales $0.0089 h \\mathrm{Mpc}^{-1}<k<0.5 h \\mathrm{Mpc}^{-1}$ and redshifts $0<z<3$. FREmu leverages Principal Component Analysis and Artificial Neural Networks to establish a mapping from parameters to power spectra, utilizing training data derived from the Quijote-MG simulation suite. With a parameter space encompassing 7 dimensions, including $\\Omega_m$, $\\Omega_b$, $h$, $n_s$, $\\sigma_8$, $M_{\\nu}$ and $f_{R_0}$, the emulator achieves an accuracy exceeding 95% for the majority of cases, thus proving to be highly efficient for constraining parameters.","url_abs":"https://arxiv.org/abs/2405.05840v2","url_pdf":"https://arxiv.org/pdf/2405.05840v2.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":"fremu-power-spectrum-emulator-for-f-r-gravity","repo_url":"https://github.com/astrobai/fremu","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","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}