FREmu: Power Spectrum Emulator for $f(R)$ Gravity
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arXiv
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| Format: | Preprint |
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2024
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| _version_ | 1866912146119458816 |
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| author | Bai, Jiachen Xia, Junqing |
| author_facet | Bai, Jiachen Xia, Junqing |
| contents | 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 $Ω_m$, $Ω_b$, $h$, $n_s$, $σ_8$, $M_ν$ 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_05840 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | FREmu: Power Spectrum Emulator for $f(R)$ Gravity Bai, Jiachen Xia, Junqing Cosmology and Nongalactic Astrophysics Instrumentation and Methods for Astrophysics 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 $Ω_m$, $Ω_b$, $h$, $n_s$, $σ_8$, $M_ν$ 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. |
| title | FREmu: Power Spectrum Emulator for $f(R)$ Gravity |
| topic | Cosmology and Nongalactic Astrophysics Instrumentation and Methods for Astrophysics |
| url | https://arxiv.org/abs/2405.05840 |