De-baryonifying halos via optimal transport

TL;DR

This paper introduces a novel method using optimal transport to remove baryonic effects from halo mass maps, improving the accuracy of weak lensing analyses by accounting for feedback uncertainties.

Contribution

It proposes a new optimal transport-based approach to de-baryonify halos, integrating feedback constraints into weak lensing field-level likelihoods.

Findings

De-baryonified halos reproduce the correct convergence power spectrum suppression.

The method shows promise for generalization to full convergence maps.

Significant scatter exists at the individual halo level.

Abstract

Baryonic feedback uncertainty is a limiting systematic for next-generation weak gravitational lensing analyses. At the same time, high-resolution weak lensing maps are best analyzed at the field-level. Thus, robustly accounting for the baryonic effects in the projected matter density field is required. Ideally, constraints on feedback strength from astrophysical probes should be folded into the weak lensing field-level likelihood. We propose a macroscopic method based on an empirical correlation between feedback strength and an optimal transport cost. Since feedback is local re-distribution of matter, optimal transport is a promising concept. In this proof-of-concept, we de-baryonify projected mass around individual halos in the IllustrisTNG simulation. We choose the de-baryonified solution as the point of maximum likelihood on the hypersurface defined by fixed optimal transport cost around the observed full-physics halos. The likelihood is approximated through a normalizing flow trained on multiple gravity-only simulations. We find that the set of de-baryonified halos reproduces the correct convergence power spectrum suppression. There is considerable scatter when considering individual halos. We outline how the optimal transport de-baryonification concept can be generalized to full convergence maps.