Cosmological forecast for non-Gaussian statistics in large-scale weak lensing surveys

Cosmic shear data contains a large amount of cosmological information encapsulated in the non-Gaussian features of the weak lensing mass maps. Weak lensing studies mostly rely on two-point statistics to constrain cosmology from cosmic shear data, that do not capture all of this information. Additional non-Gaussian information can be extracted using non-Gaussian statistics. We compare the constraining power in the Ωm–σ8 plane of three map-based non-Gaussian statistics with the angular power spectrum, namely; peak counts, minimum counts and Minkowski functionals. We further analyze the impact of tomography and systematic effects originating from galaxy intrinsic alignments, multiplicative shear bias and photometric redshift systematics. We forecast the performance of the statistics for a stage-3-like weak lensing survey, spanning an area of 5000 deg2 and restrict ourselves to scales ≥ 10 arcmin to avoid baryonic effects. The study follows a forward modelling scheme to predict the statistics at different cosmologies based on N-Body simulations. We find, that in our setup, the considered non-Gaussian statistics provide tighter constraints than the angular power spectrum. The peak counts show the greatest potential, increasing the figure-of-Merit (FoM) in the Ωm–σ8 plane by a factor of about 6, while the minimum counts and the Minkowski functionals yield an increase by a factor of about 3 and 2, respectively. A combined analysis using all non-Gaussian statistics in addition to the power spectrum increases the FoM by a factor of 9 and reduces the error on S8 by ≈ 30%. We find that the importance of tomography is diminished when combining non-Gaussian statistics with the angular power spectrum. The non-Gaussian statistics indeed profit less from tomography and the minimum counts and Minkowski functionals add some robustness against galaxy intrinsic alignment in a non-tomographic setting. We further find that a combination of the angular power spectrum and the non-Gaussian statistics allows us to apply conservative scale cuts in the analysis, thus helping to minimize the impact of baryonic and relativistic effects, while conserving the cosmological constraining power. We make the code that was used to conduct this analysis publicly available to simplify performing such analyses in the future. © 2021 IOP PublishingISSN:1475-751