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| Auteurs principaux: | , , , , |
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| Format: | Preprint |
| Publié: |
2024
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| Sujets: | |
| Accès en ligne: | https://arxiv.org/abs/2403.13985 |
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| _version_ | 1866910677644345344 |
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| author | Yip, Jacky H. T. Biagetti, Matteo Cole, Alex Viswanathan, Karthik Shiu, Gary |
| author_facet | Yip, Jacky H. T. Biagetti, Matteo Cole, Alex Viswanathan, Karthik Shiu, Gary |
| contents | Persistent homology naturally addresses the multi-scale topological characteristics of the large-scale structure as a distribution of clusters, loops, and voids. We apply this tool to the dark matter halo catalogs from the Quijote simulations, and build a summary statistic for comparison with the joint power spectrum and bispectrum statistic regarding their information content on cosmological parameters and primordial non-Gaussianity. Through a Fisher analysis, we find that constraints from persistent homology are tighter for 8 out of the 10 parameters by margins of 13-50%. The complementarity of the two statistics breaks parameter degeneracies, allowing for a further gain in constraining power when combined. We run a series of consistency checks to consolidate our results, and conclude that our findings motivate incorporating persistent homology into inference pipelines for cosmological survey data. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_13985 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Cosmology with Persistent Homology: a Fisher Forecast Yip, Jacky H. T. Biagetti, Matteo Cole, Alex Viswanathan, Karthik Shiu, Gary Cosmology and Nongalactic Astrophysics High Energy Physics - Theory Algebraic Topology Persistent homology naturally addresses the multi-scale topological characteristics of the large-scale structure as a distribution of clusters, loops, and voids. We apply this tool to the dark matter halo catalogs from the Quijote simulations, and build a summary statistic for comparison with the joint power spectrum and bispectrum statistic regarding their information content on cosmological parameters and primordial non-Gaussianity. Through a Fisher analysis, we find that constraints from persistent homology are tighter for 8 out of the 10 parameters by margins of 13-50%. The complementarity of the two statistics breaks parameter degeneracies, allowing for a further gain in constraining power when combined. We run a series of consistency checks to consolidate our results, and conclude that our findings motivate incorporating persistent homology into inference pipelines for cosmological survey data. |
| title | Cosmology with Persistent Homology: a Fisher Forecast |
| topic | Cosmology and Nongalactic Astrophysics High Energy Physics - Theory Algebraic Topology |
| url | https://arxiv.org/abs/2403.13985 |