English

Approximating Density Probability Distribution Functions Across Cosmologies

Cosmology and Nongalactic Astrophysics 2022-04-27 v1 Astrophysics of Galaxies

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: nsn_s, the spectral slope, and σL\sigma_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, sL=(dvpecL/dr)2/Hs_L={\sqrt{\langle(dv^L_{\rm pec}/dr)^2\rangle}}/{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.

Keywords

Cite

@article{arxiv.2109.06194,
  title  = {Approximating Density Probability Distribution Functions Across Cosmologies},
  author = {Huanqing Chen and Nickolay Y. Gnedin and Philip Mansfield},
  journal= {arXiv preprint arXiv:2109.06194},
  year   = {2022}
}

Comments

9 pages, 10 figures, submitted to ApJ, comments welcome

R2 v1 2026-06-24T05:55:49.041Z