Scattering transforms on the sphere, application to large scale structure modelling

TL;DR

This paper develops spherical scattering transforms to model complex astrophysical fields, enabling effective generative models for large-scale structure analysis in cosmology.

Contribution

It introduces the extension of scattering transforms to the sphere and demonstrates their use in creating maximum-entropy generative models for astrophysical data.

Findings

Generative models are statistically accurate and visually convincing.

Spherical scattering transforms effectively capture non-Gaussian features.

The approach opens new avenues for cosmological data analysis.

Abstract

Scattering transforms are a new type of summary statistics recently developed for the study of highly non-Gaussian processes, which have been shown to be very promising for astrophysical studies. In particular, they allow one to build generative models of complex non-linear fields from a limited amount of data. In the context of upcoming cosmological surveys, the extension of these tools to spherical data is necessary. We develop scattering transforms on the sphere and focus on the construction of maximum-entropy generative models of astrophysical fields. The quality of the generative models, both statistically and visually, is very satisfying, which therefore open up a wide range of new applications for future cosmological studies.