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General framework for cosmological dark matter bounds using N-body simulations
Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC).
Stockholm University, Faculty of Science, Department of Physics. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). University College London, UK.ORCID iD: 0000-0002-2519-584X
Number of Authors: 22021 (English)In: Physical Review D: covering particles, fields, gravitation, and cosmology, ISSN 2470-0010, E-ISSN 2470-0029, Vol. 103, no 4, article id 043526Article in journal (Refereed) Published
Abstract [en]

We present a general framework for obtaining robust bounds on the nature of dark matter using cosmological N-body simulations and Lyman-alpha forest data. We construct an emulator of hydrodynamical simulations, which is a flexible, accurate and computationally efficient model for predicting the response of the Lyman-alpha forest flux power spectrum to different dark matter models, the state of the intergalactic medium (IGM) and the primordial power spectrum. The emulator combines a flexible parametrization for the small-scale suppression in the matter power spectrum arising in noncold dark matter models, with an improved IGM model. We then demonstrate how to optimize the emulator for the case of ultralight axion dark matter, presenting tests of convergence. We also carry out cross-validation tests of the accuracy of flux power spectrum prediction. This framework can be optimized for the analysis of many other dark matter candidates, e.g., warm or interacting dark matter. Our work demonstrates that a combination of an optimized emulator and cosmological effective theories, where many models are described by a single set of equations, is a powerful approach for robust and computationally efficient inference from the cosmic large-scale structure.

Place, publisher, year, edition, pages
2021. Vol. 103, no 4, article id 043526
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Physical Sciences
Identifiers
URN: urn:nbn:se:su:diva-192462DOI: 10.1103/PhysRevD.103.043526ISI: 000620020600002OAI: oai:DiVA.org:su-192462DiVA, id: diva2:1546532
Available from: 2021-04-22 Created: 2021-04-22 Last updated: 2022-02-25Bibliographically approved

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Rogers, Keir K.Peiris, Hiranya V.

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