Cosmological Forecast for non-Gaussian Statistics in large-scale weak Lensing Surveys

TL;DR

This paper demonstrates that non-Gaussian statistics of weak lensing maps, especially peak counts, significantly improve cosmological parameter constraints over traditional power spectrum analysis, with robustness benefits and practical analysis strategies.

Contribution

It compares the constraining power of three non-Gaussian statistics with the power spectrum and shows their combined benefits for stage-3 weak lensing surveys.

Findings

Non-Gaussian statistics outperform power spectrum in constraining mbda_m - mbda_8.

Peak counts increase the Figure-of-Merit by a factor of about 4.

Combining all statistics increases FoM by a factor of 5 and reduces _ error by 5%.

Abstract

Cosmic shear data contains a large amount of cosmological information encapsulated in the non-Gaussian features of the weak lensing mass maps. This information can be extracted using non-Gaussian statistics. We compare the constraining power in the $\Omega_{\mathrm{m}} - \sigma_8$ plane of three map-based non-Gaussian statistics with the angular power spectrum, namely; peak/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 and restrict ourselves to scales $\geq$ 10 arcmin. 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 $\Omega_{\mathrm{m}} - \sigma_8$ plane by a factor of about 4. A combined analysis using all non-Gaussian statistics in addition to the power spectrum increases the FoM by a factor of 5 and reduces the error on $S_8$ by $\approx$ 25\%. 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.