Cosmological Model Parameter Dependence of the Matter Power Spectrum Covariance from the DEUS-PUR $Cosmo$ Simulations
Linda Blot, Pier-Stefano Corasaniti, Yann Rasera, Shankar Agarwal

TL;DR
This study investigates how the matter power spectrum covariance depends on cosmological parameters using extensive N-body simulations, highlighting the importance of modeling this dependence for accurate cosmological inference.
Contribution
It provides the first detailed analysis of the cosmological dependence of the matter power spectrum covariance using the DEUS-PUR simulations, including derivatives and impact on parameter errors.
Findings
Variations in covariance can reach 150% depending on scale and redshift.
Fixing covariance to a fiducial cosmology biases parameter errors.
Modeling covariance dependence improves parameter estimation accuracy.
Abstract
Future galaxy surveys will provide accurate measurements of the matter power spectrum across an unprecedented range of scales and redshifts. The analysis of these data will require one to accurately model the imprint of non-linearities of the matter density field. In particular, these induce a non-Gaussian contribution to the data covariance that needs to be properly taken into account to realise unbiased cosmological parameter inference analyses. Here, we study the cosmological dependence of the matter power spectrum covariance using a dedicated suite of N-body simulations, the Dark Energy Universe Simulation - Parallel Universe Runs (DEUS-PUR) {\it Cosmo}. These consist of 512 realizations for 10 different cosmologies where we vary the matter density , the amplitude of density fluctuations , the reduced Hubble parameter and a constant dark energy equation of…
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