Περίληψη :
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. In this talk, I will discuss recent efforts to achieve this task using the Wavelet Scattering Transform (WST), which subjects an input field to a layer of non-linear transformations that are sensitive to non-Gaussianity through a generated set of WST coefficients. In order to assess its applicability in the context of LSS surveys, I will present the first WST application to actual galaxy observations, through a WST re-analysis of the BOSS DR12 CMASS dataset. After laying out the procedure on how to capture all necessary layers of realism for an application to data obtained from a spectroscopic survey, I will show results for the marginalized posterior probability distributions of multiple cosmological parameters obtained from a likelihood analysis of the CMASS data. A joint WST+ 2-point correlation function (2pcf) analysis is found to deliver a substantial improvement in the values of the predicted 1σ errors compared to the regular 2pcf-only analysis, highlighting the exciting prospect of employing higher-order statistics in order to fully exploit the potential of upcoming Stage-IV spectroscopic observations from DESI and Euclid.
