Constraining modified gravity with weak lensing peaks
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arXiv
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| Autores principales: | , , , , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| _version_ | 1866909275838742528 |
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| author | Davies, Christopher T. Harnois-Déraps, Joachim Li, Baojiu Giblin, Benjamin Hernández-Aguayo, César Paillas, Enrique |
| author_facet | Davies, Christopher T. Harnois-Déraps, Joachim Li, Baojiu Giblin, Benjamin Hernández-Aguayo, César Paillas, Enrique |
| contents | It is well established that maximizing the information extracted from upcoming and ongoing stage-IV weak-lensing surveys requires higher-order summary statistics that complement the standard two-point statistics. In this work, we focus on weak-lensing peak statistics to test two popular modified gravity models, $f(R)$ and nDGP, using the FORGE and BRIDGE weak-lensing simulations, respectively. From these simulations we measure the peak statistics as a function of both cosmological and modified gravity parameters simultaneously. Our findings indicate that the peak abundance is sensitive to the strength of modified gravity, while the peak two-point correlation function is sensitive to the nature of the screening mechanism in a modified gravity model. We combine these simulated statistics with a Gaussian Process Regression emulator and a Gaussian likelihood to generate stage-IV forecast posterior distributions for the modified gravity models. We demonstrate that, assuming small scales can be correctly modelled, peak statistics can be used to distinguish GR from $f(R)$ and nDGP models at the two-sigma level with a stage-IV survey area of $300 \, \rm{deg}^2$ and $1000 \, \rm{deg}^2$, respectively. Finally, we show that peak statistics can constrain $\log_{10}\left(|f_{R0}|\right) = -6$ to 2\% precision, and $\log_{10}(H_0 r_c) = 0.5$ to 25\% precision. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_11958 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Constraining modified gravity with weak lensing peaks Davies, Christopher T. Harnois-Déraps, Joachim Li, Baojiu Giblin, Benjamin Hernández-Aguayo, César Paillas, Enrique Cosmology and Nongalactic Astrophysics It is well established that maximizing the information extracted from upcoming and ongoing stage-IV weak-lensing surveys requires higher-order summary statistics that complement the standard two-point statistics. In this work, we focus on weak-lensing peak statistics to test two popular modified gravity models, $f(R)$ and nDGP, using the FORGE and BRIDGE weak-lensing simulations, respectively. From these simulations we measure the peak statistics as a function of both cosmological and modified gravity parameters simultaneously. Our findings indicate that the peak abundance is sensitive to the strength of modified gravity, while the peak two-point correlation function is sensitive to the nature of the screening mechanism in a modified gravity model. We combine these simulated statistics with a Gaussian Process Regression emulator and a Gaussian likelihood to generate stage-IV forecast posterior distributions for the modified gravity models. We demonstrate that, assuming small scales can be correctly modelled, peak statistics can be used to distinguish GR from $f(R)$ and nDGP models at the two-sigma level with a stage-IV survey area of $300 \, \rm{deg}^2$ and $1000 \, \rm{deg}^2$, respectively. Finally, we show that peak statistics can constrain $\log_{10}\left(|f_{R0}|\right) = -6$ to 2\% precision, and $\log_{10}(H_0 r_c) = 0.5$ to 25\% precision. |
| title | Constraining modified gravity with weak lensing peaks |
| topic | Cosmology and Nongalactic Astrophysics |
| url | https://arxiv.org/abs/2406.11958 |