%0 Generic %1 chen2021approximating %A Chen, Huanqing %A Gnedin, Nickolay Y. %A Mansfield, Philip %D 2021 %K library %T Approximating Density Probability Distribution Functions Across Cosmologies %U http://arxiv.org/abs/2109.06194 %X 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, $s_L=łangle(dv^L_pec/dr)^2\rangle/H$. 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.

@misc{chen2021approximating, 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.}, added-at = {2021-09-15T15:11:40.000+0200}, author = {Chen, Huanqing and Gnedin, Nickolay Y. and Mansfield, Philip}, biburl = {https://www.bibsonomy.org/bibtex/2417b1cd5068b6fc73c9c27fed2eddcfa/gpkulkarni}, description = {Approximating Density Probability Distribution Functions Across Cosmologies}, interhash = {496c1cf3c761f3efffd620e8576ac2cc}, intrahash = {417b1cd5068b6fc73c9c27fed2eddcfa}, keywords = {library}, note = {cite arxiv:2109.06194Comment: 9 pages, 10 figures, submitted to ApJ, comments welcome}, timestamp = {2021-09-15T15:11:40.000+0200}, title = {Approximating Density Probability Distribution Functions Across Cosmologies}, url = {http://arxiv.org/abs/2109.06194}, year = 2021 }