Approximating Density Probability Distribution Functions Across Cosmologies
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: , the spectral slope, and , the linear rms density fluctuation. For redshift-space density and the geometric mean of real- and redshift-space densities, we introduce a third parameter, . 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.
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