Normalizing flows for random fields in cosmology

Understand

Normalizing flows are a powerful tool to create flexible probability distributions with a wide range of potential applications in cosmology.

• Here we are studying normalizing flows which represent cosmological observables at field level, rather than at the level of summary statistics such as the power spectrum.
• We evaluate the performance of different normalizing flows for both density estimation and sampling of near-Gaussian random fields, and check the quality of samples with different statistics such as power spectrum and bispectrum estimators.
• We explore aspects of these flows that are specific to cosmology, such as flowing from a physical prior distribution and evaluating the density estimation results in the analytically tractable correlated Gaussian case.