Fisher for complements: Extracting cosmology and neutrino mass from the counts-in-cells PDF
Cora Uhlemann, Oliver Friedrich, Francisco Villaescusa-Navarro, Arka, Banerjee, Sandrine Codis

TL;DR
This paper analyzes the cosmology dependence of counts-in-cell statistics, especially the matter PDF, to improve constraints on cosmological parameters and neutrino mass using simulations and Fisher forecasts.
Contribution
It introduces a formalism linking the matter PDF to cosmological parameters, including massive neutrinos, and demonstrates its effectiveness in constraining these parameters.
Findings
Matter PDF is highly sensitive to neutrino mass $M_\nu$.
Combining matter PDF with power spectrum improves parameter constraints.
Total neutrino mass can be constrained to better than 0.01 eV with large volume data.
Abstract
We comprehensively analyse the cosmology dependence of counts-in-cell statistics. We focus on the shape of the one-point probability distribution function (PDF) of the matter density field at mildly nonlinear scales. Based on large-deviation statistics, we parametrise the cosmology dependence of the matter PDF in terms of the linear power spectrum, the growth factor, the spherical collapse dynamics, and the nonlinear variance. We extend our formalism to include massive neutrinos, finding that the total matter PDF is highly sensitive to the total neutrino mass and can disentangle it from the clustering amplitude . Using more than a million PDFs extracted from the Quijote simulations, we determine the response of the matter PDF to changing parameters in the CDM model and successfully cross-validate the theoretical model and the simulation measurements. We…
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Taxonomy
TopicsGalaxies: Formation, Evolution, Phenomena · Cosmology and Gravitation Theories · Statistical Mechanics and Entropy
