Work

Approximating Density Probability Distribution Functions Across Cosmologies

Year: 2022

Type: article

Abstract: Using a suite of self-similar cosmological simulations, we measure the probability distribution functions (PDFs) of real-space density, redshift-space density, and their geometric mean. We find that the real-space density PDF is well-described by a function of two parameters: n s , the spectral slope, and σ L , the linear rms density fluctuation. For redshift-space density and the geometric mean of real- and redshift-space densities, we introduce a third parameter, <?CDATA ${s}_{L}=\sqrt{\langle {\left({{dv}}_{\mathrm{pec}}^{L}/{dr}\right)}^{2}\rangle }/H$?> s L = 〈 dv pec L / dr 2 〉 / H . We find that density PDFs for the LCDM cosmology is also well-parameterized by these three parameters. As a result, we are able to use a suite of self-similar cosmological simulations to approximate density PDFs for a range of cosmologies. We make the density PDFs publicly available and provide an analytical fitting formula for them.

Source: The Astrophysical Journal

DOI: 10.3847/1538-4357/ac5e9f

Authors: Huanqing Chen, Nickolay Y. Gnedin, Philip Mansfield

Institutions: University of Chicago, Fermi National Accelerator Laboratory, Kavli Institute for Particle Astrophysics and Cosmology, Stanford University

Language: English

Topic: Galaxies: Formation, Evolution, Phenomena

Subfield: Astronomy and Astrophysics

Field: Physics and Astronomy

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $4,499

Funders: U.S. Department of Energy, National Aeronautics and Space Administration, Office of Science, High Energy Physics