Enhancing cosmic shear with the multi-scale lensing PDF
Benjamin Giblin, Yan-Chuan Cai, Joachim Harnois-D\'eraps

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 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 than the two-point shear correlation functions. For Stage-IV surveys, we achieve 90\% tighter constraints on , but also on the Hubble and dark energy equation of state parameters. Interestingly, we find improvements when combining these two…
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Taxonomy
TopicsGalaxies: Formation, Evolution, Phenomena · Astronomy and Astrophysical Research · Cosmology and Gravitation Theories
