CFHTLenS: A Gaussian likelihood is a sufficient approximation for a cosmological analysis of third-order cosmic shear statistics
P. Simon, E. Semboloni, L. van Waerbeke, H. Hoekstra, T. Erben, L. Fu,, J. Harnois-D\'eraps, C. Heymans, H. Hildebrandt, M. Kilbinger, T.D. Kitching,, L. Miller, T. Schrabback

TL;DR
This study evaluates the adequacy of Gaussian likelihood models for third-order cosmic shear statistics in cosmology, finding they are reasonable for current surveys but may be insufficient for future, more precise data.
Contribution
The paper introduces a non-Gaussian likelihood model supported by simulations and proposes an algorithm for refined analysis and data compression in cosmic shear studies.
Findings
Gaussian likelihood is a reasonable approximation for CFHTLenS-like surveys
The non-Gaussian model provides a good fit but with moderate discrepancies
Identifies potential systematics affecting shear signal at certain scales
Abstract
We study the correlations of the shear signal between triplets of sources in the Canada-France-Hawaii Lensing Survey (CFHTLenS) to probe cosmological parameters via the matter bispectrum. In contrast to previous studies, we adopted a non-Gaussian model of the data likelihood which is supported by our simulations of the survey. We find that for state-of-the-art surveys, similar to CFHTLenS, a Gaussian likelihood analysis is a reasonable approximation, albeit small differences in the parameter constraints are already visible. For future surveys we expect that a Gaussian model becomes inaccurate. Our algorithm for a refined non-Gaussian analysis and data compression is then of great utility especially because it is not much more elaborate if simulated data are available. Applying this algorithm to the third-order correlations of shear alone in a blind analysis, we find a good agreement…
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