Dark Energy Survey Year 3 results: cosmology with moments of weak lensing mass maps -- validation on simulations

TL;DR

This paper demonstrates that combining second and third moments of weak lensing mass maps enhances cosmological parameter constraints, capturing non-Gaussian information and outperforming traditional shear 2-point analyses.

Contribution

The paper introduces a formalism for extracting and analyzing second and third moments of convergence maps from weak lensing data, validated through simulations for DES Y3.

Findings

Combining moments yields 1.5% constraint on S_8.

Including third moments improves constraints by 20%.

Methodology is applicable to current and future weak lensing surveys.

Abstract

We present a simulated cosmology analysis using the second and third moments of the weak lensing mass (convergence) maps. The analysis is geared towards the third year (Y3) data from the Dark Energy Survey (DES), but the methodology can be applied to other weak lensing data sets. The second moment, or variances, of the convergence as a function of smoothing scale contains information similar to standard shear 2-point statistics. The third moment, or the skewness, contains additional non-Gaussian information. We present the formalism for obtaining the convergence maps from the measured shear and for obtaining the second and third moments of these maps given partial sky coverage. We estimate the covariance matrix from a large suite of numerical simulations. We test our pipeline through a simulated likelihood analyses varying 5 cosmological parameters and 10 nuisance parameters. Our forecast shows that the combination of second and third moments provides a 1.5 percent constraint on $S_8 \equiv \sigma_8 (\Omega_{\rm m}/0.3)^{0.5}$ for DES Y3 data. This is 20 percent better than an analysis using a simulated DES Y3 shear 2-point statistics, owing to the non-Gaussian information captured by the inclusion of higher-order statistics. The methodology developed here can be applied to current and future weak lensing datasets to make use of information from non-Gaussianity in the cosmic density field and to improve constraints on cosmological parameters.