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arXiv · 2109.06194

Approximating Density Probability Distribution Functions Across Cosmologies

Huanqing Chen·Nickolay Y. Gnedin·Philip Mansfield
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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 $\sigma_L$, the linear rms density fluctuation. For redshift-space density and the geometric mean of real- and redshift-space densities, we introduce a third parameter, $s_L={\sqrt{\langle(dv^L_{\rm pec}/dr)^2\rangle}}/{H}$. 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.

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Huanqing Chen, Nickolay Y. Gnedin, Philip Mansfield. 2021-09-13. Approximating Density Probability Distribution Functions Across Cosmologies. https://doi.org/10.3847/1538-4357%2Fac5e9f

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