From Weak Lensing to non-Gaussianity via Minkowski Functionals
Dipak Munshi, Ludovic van Waerbeke, Joseph Smidt, Peter Coles

TL;DR
This paper introduces a harmonic-domain method to extract Minkowski Functionals from weak lensing maps, enabling better analysis of non-Gaussian features and separation of late-time and primordial non-Gaussianity.
Contribution
It develops a novel harmonic-based approach for Minkowski Functional estimation, extending skewness parameters to skew-spectra, and compares different bispectrum models for weak lensing.
Findings
Harmonic approach effectively handles masks and noise.
Skew-spectra provide more information than one-point statistics.
Separation of late-time and primordial non-Gaussianity depends on redshift and scale.
Abstract
We present a new harmonic-domain approach for extracting morphological information, in the form of Minkowski Functionals (MFs), from weak lensing (WL) convergence maps. Using a perturbative expansion of the MFs, which is expected to be valid for the range of angular scales probed by most current weak-lensing surveys, we show that the study of three generalized skewness parameters is equivalent to the study of the three MFs defined in two dimensions. We then extend these skewness parameters to three associated skew-spectra which carry more information about the convergence bispectrum than their one-point counterparts. We discuss various issues such as noise and incomplete sky coverage in the context of estimation of these skew-spectra from realistic data. Our technique provides an alternative to the pixel-space approaches typically used in the estimation of MFs, and it can be…
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