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Título

Density distribution of the cosmological matter field

AutorKlypin, Anatoly; Prada, Francisco CSIC ORCID ; Betancort-Rijo, J.; Albareti, F. D.
Palabras claveCosmology: Large-scale structure
Dark matter
Galaxies: haloes
Methods: numerical
Fecha de publicación2018
EditorOxford University Press
CitaciónMonthly Notices of the Royal Astronomical Society 481: 4588-4601 (2018)
ResumenThe one-point probability distribution function (PDF) of thematter density field in the universe is a fundamental property that plays an essential role in cosmology for estimates such as gravitational weak lensing, non-linear clustering, massive production of mock galaxy catalogues, and testing predictions of cosmological models. Here we make a comprehensive analysis of the dark matter PDF, using a suite of ~7000 N-body simulations that covers a wide range of numerical and cosmological parameters. We find that the PDF has a simple shape: it declines with density as a power-law P ∝ ρ , which is exponentially suppressed on both small and large densities. The proposed double-exponential approximation provides an accurate fit to all our N-body results for small filtering scales R < 5 h Mpc with rms density fluctuations σ > 1. In combination with the spherical infall model that works well for small fluctuations σ < 1, the PDF is now approximated with just few per cent errors over the range of 12 orders of magnitude - a remarkable example of precision cosmology. We find that at ~5-10 per cent level the PDF explicitly depends on redshift (at fixed s) and on cosmological density parameter Ω. We test different existing analytical approximations and find that the often-used lognormal approximation is always 3-5 times less accurate than either the double-exponential approximation or the spherical infall model.© 2018 The Author(s). Published by Oxford University Press on behalf of the Royal Astronomical Society.
Versión del editorhttp://dx.doi.org/10.1093/MNRAS/STY2613
URIhttp://hdl.handle.net/10261/206714
DOI10.1093/MNRAS/STY2613
Identificadoresdoi: 10.1093/MNRAS/STY2613
issn: 1365-2966
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