Enhancing cosmic shear with the multi-scale lensing PDF

TL;DR

This paper demonstrates that multi-scale lensing PDFs, modeled with an emulator trained on simulations, significantly improve cosmological parameter constraints over traditional two-point statistics, especially for future surveys.

Contribution

The study introduces a numerical emulator for the lensing PDF, showing multi-scale PDFs provide substantial non-Gaussian information and outperform two-point statistics in constraining cosmological parameters.

Findings

33% tighter constraints on S8 for Stage-III surveys

Over 90% tighter constraints on S8, Hubble, and dark energy parameters for Stage-IV surveys

Lensing PDFs contain all information from two-point statistics and more in future surveys.

Abstract

We quantify the cosmological constraining power of the `lensing PDF' - the one-point probability density of weak lensing convergence maps - by modelling this statistic numerically with an emulator trained on $w$CDM cosmic shear simulations. After validating our methods on Gaussian and lognormal fields, we show that `multi-scale' PDFs - measured from maps with multiple levels of smoothing - offer considerable gains over two-point statistics, owing to their ability to extract non-Gaussian information: for a mock Stage-III survey, lensing PDFs yield 33\% tighter constraints on the clustering parameter $S_8=\sigma_8\sqrt{\Omega_{\rm m}/0.3}$ than the two-point shear correlation functions. For Stage-IV surveys, we achieve $>$90\% tighter constraints on $S_8$, but also on the Hubble and dark energy equation of state parameters. Interestingly, we find improvements when combining these two probes only in our Stage-III setup; in the Stage-IV scenario the lensing PDFs contain all information from the standard two-point statistics and more. This suggests that while these two probes are currently complementary, the lower noise levels of upcoming surveys will unleash the constraining power of the PDF.