Multiscale Flow for Robust and Optimal Cosmological Analysis

arXiv:2306.04689v2 Announce Type: replace-cross
Abstract: We propose Multiscale Flow, a generative Normalizing Flow that creates samples and models the field-level likelihood of two-dimensional cosmological data such as weak lensing. Multiscale Flow uses hierarchical decomposition of cosmological fields via a wavelet basis, and then models different wavelet components separately as Normalizing Flows. The log-likelihood of the original cosmological field can be recovered by summing over the log-likelihood of each wavelet term. This decomposition allows us to separate the information from different …

abstract analysis arxiv astro-ph.co components cs.lg data fields flow generative hierarchical likelihood physics.data-an robust samples type via wavelet