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Persistent homology in cosmic shear. II. A tomographic analysis of DES-Y1

Abstract : We demonstrate how to use persistent homology for cosmological parameter inference in a tomographic cosmic shear survey. We obtain the first cosmological parameter constraints from persistent homology by applying our method to the first-year data of the Dark Energy Survey. To obtain these constraints, we analyse the topological structure of the matter distribution by extracting persistence diagrams from signal-to-noise maps of aperture masses. This presents a natural extension to the widely used peak count statistics. Extracting the persistence diagrams from the cosmo-SLICS, a suite of N-body simulations with variable cosmological parameters, we interpolate the signal using Gaussian processes and marginalise over the most relevant systematic effects, including intrinsic alignments and baryonic effects. For the structure growth parameter, we find S8 = 0.747−0.031+0.025, which is in full agreement with other late-time probes. We also constrain the intrinsic alignment parameter to A = 1.54 ± 0.52, which constitutes a detection of the intrinsic alignment effect at almost 3σ.
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https://hal-insu.archives-ouvertes.fr/insu-03863227
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Submitted on : Monday, November 21, 2022 - 1:30:22 PM
Last modification on : Tuesday, November 22, 2022 - 3:22:19 AM

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Distributed under a Creative Commons Attribution 4.0 International License

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Sven Heydenreich, Benjamin Brück, Pierre Burger, Joachim Harnois-Déraps, Sandra Unruh, et al.. Persistent homology in cosmic shear. II. A tomographic analysis of DES-Y1. Astronomy and Astrophysics - A&A, 2022, 667, ⟨10.1051/0004-6361/202243868⟩. ⟨insu-03863227⟩

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