Optimal Capture of Non-Gaussianity in Weak-Lensing Surveys: Power Spectrum, Bispectrum, and Halo Counts

We compare the efficiency of weak-lensing-selected galaxy cluster 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 Ω m –σ 8 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, and counts as a function of clusters' mass and redshift. We show that when combined with the power spectrum, those four kinds of counts provide similar constraints, thus allowing one to perform the most direct counts, signal-to-noise peak counts, and get percent level constraints on cosmological parameters. We show that the weak-lensing bispectrum gives constraints comparable to those given by the power spectrum and captures non-Gaussian features as well as cluster counts, its combination with the power spectrum giving errors on cosmological parameters that are similar to, if not marginally smaller than, those obtained when combining the power spectrum with cluster counts. We finally note that in order to reach its potential, the weak-lensing bispectrum must be computed using all triangle configurations, as equilateral triangles alone do not provide useful information. The appendices summarize the halo model, and the way the power spectrum and bispectrum are computed in this framework.