Optimal capture of non-Gaussianity in weak lensing surveys: power spectrum, bispectrum and halo counts
Joel Berge, Adam Amara, Alexandre Refregier

TL;DR
This paper compares the effectiveness of weak lensing-selected galaxy cluster counts and the bispectrum in capturing non-Gaussian features of the dark matter distribution, demonstrating their combined potential for precise cosmological constraints.
Contribution
It introduces a comprehensive analysis of weak lensing power spectrum, bispectrum, and cluster counts, highlighting their combined utility in constraining cosmological parameters.
Findings
Cluster counts and bispectrum provide similar constraints when combined with the power spectrum.
The bispectrum captures non-Gaussian features as effectively as cluster counts.
Using all triangle configurations enhances the bispectrum's potential for cosmological insights.
Abstract
We compare the efficiency of weak lensing-selected galaxy clusters counts and of the weak lensing bispectrum at capturing non-Gaussian features in the dark matter distribution. We use the halo model to compute the weak lensing power spectrum, the bispectrum and the expected number of detected clusters, and derive constraints on cosmological parameters for a large, low systematic weak lensing survey, by focusing on the - plane and on the dark energy equation of state. We separate the power spectrum into the resolved and the unresolved parts of the data, the resolved part being defined as detected clusters, and the unresolved part as the rest of the field. We consider four kinds of clusters counts, taking into account different amount of information : signal-to-noise ratio peak counts; counts as a function of clusters' mass; counts as a function of clusters' redshift;…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
