Enhancing cosmic shear with the multi-scale lensing PDF

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 $S_8={\sigma }_8\sqrt{{\Omega }_{\mathrm{m}}/0.3}$ 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.

18 pages, 9 figures, accepted for publication in MNRAS

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• Dark Energy Survey Year 3 Results: Cosmological constraints from second and third-order shear statistics
• MF-Box: Multi-fidelity and multi-scale emulation for the matter power spectrum
• Stage IV baryonic feedback correction for non-Gaussianity inference
• Cosmological constraints from HSC Y1 lensing convergence PDF
• Neural style transfer of weak lensing mass maps
• Turning dispersion into signal: density-split analyses of pairwise velocities
• Non-linear infusion of intrinsic alignment and source clustering: impact on non-Gaussian cosmic shear statistics