Towards an Optimal Estimation of Cosmological Parameters with the Wavelet Scattering Transform

TL;DR

This paper demonstrates that the Wavelet Scattering Transform significantly improves the precision of cosmological parameter estimation from large-scale structure data compared to traditional methods, showing promise for future galaxy surveys.

Contribution

It introduces the use of the Wavelet Scattering Transform for 3D cosmological data analysis, achieving substantial improvements in parameter constraints over standard power spectrum methods.

Findings

WST yields 1.2-4x tighter parameter errors than power spectrum.

50% improvement in neutrino mass constraints over marked power spectrum.

First application of WST on 3D cosmological fields.

Abstract

Optimal extraction of the non-Gaussian information encoded in the Large-Scale Structure (LSS) of the universe lies at the forefront of modern precision cosmology. We propose achieving this task through the use of the Wavelet Scattering Transform (WST), which subjects an input field to a layer of non-linear transformations that are sensitive to non-Gaussianity in spatial density distributions through a generated set of WST coefficients. In order to assess its applicability in the context of LSS surveys, we apply the WST on the 3D overdensity field obtained by the Quijote simulations, out of which we extract the Fisher information in 6 cosmological parameters. It is subsequently found to deliver a large improvement in the marginalized errors on all parameters, ranging between $1.2-4\times$ tighter than the corresponding ones obtained from the regular 3D cold dark matter + baryon power spectrum, as well as a $50 \%$ improvement over the neutrino mass constraint given by the marked power spectrum. Through this first application on 3D cosmological fields, we demonstrate the great promise held by this novel statistic and set the stage for its future application to actual galaxy observations.