One-point statistics matter in extended cosmologies

TL;DR

This paper shows that the one-point probability distribution function of matter density fields contains significant non-Gaussian information, greatly enhancing constraints on cosmological models and gravity beyond traditional two-point statistics.

Contribution

It extends Large Deviation Theory to predict the matter PDF in extended cosmologies and demonstrates its effectiveness in improving parameter constraints and detecting deviations from General Relativity.

Findings

Adding the matter PDF halves uncertainties on dark energy parameters.

Matter PDF increases detection significance of deviations from GR by up to six times.

Combining matter PDF with power spectrum improves cosmological parameter constraints.

Abstract

The late universe contains a wealth of information about fundamental physics and gravity, wrapped up in non-Gaussian fields. To make use of as much information as possible it is necessary to go beyond two-point statistics. Rather than going to higher order N-point correlation functions, we demonstrate that the probability distribution function (PDF) of spheres in the matter field (a one-point function) already contains a significant amount of this non-Gaussian information. The matter PDF dissects different density environments which are lumped together in two-point statistics, making it particularly useful for probing modifications of gravity or expansion history. Our approach in Cataneo et. al. 2021 extends the success of Large Deviation Theory for predicting the matter PDF in $\Lambda$CDM in these ''extended'' cosmologies. A Fisher forecast demonstrates the information content in the matter PDF via constraints for a Euclid-like survey volume combining the 3D matter PDF with the 3D matter power spectrum. Adding the matter PDF halves the uncertainties on parameters in an evolving dark energy model, relative to the power spectrum alone. Additionally, the matter PDF contains enough non-linear information to substantially increase the detection significance of departures from General Relativity, with improvements up to six times the power spectrum alone. This analysis demonstrates that the matter PDF is a promising non-Gaussian statistic for extracting cosmological information, particularly for beyond $\Lambda$CDM models.