Cross-correlating Sunyaev-Zel'dovich and Weak Lensing Maps
Dipak Munshi, Shahab Joudaki, Peter Coles, Joseph Smidt, Scott T. Kay

TL;DR
This paper develops advanced statistical tools to analyze the non-Gaussian correlation between Sunyaev-Zel'dovich and weak lensing maps, enabling detailed study of large-scale structure evolution.
Contribution
It introduces a hierarchy of mixed higher-order statistics and analytical expressions for joint PDFs, advancing cross-correlation analysis of tSZ and weak lensing data.
Findings
Derived analytical joint PDFs for tSZ and lensing maps.
Presented results for different angular smoothing scales.
Applied hierarchical, perturbative, and lognormal models.
Abstract
We present novel statistical tools to cross-correlate frequency cleaned thermal Sunyaev-Zel'dovich (tSZ) maps and tomographic weak lensing (wl) convergence maps. Moving beyond the lowest order cross-correlation, we introduce a hierarchy of mixed higher-order statistics, the cumulants and cumulant correlators, to analyze non-Gaussianity in real space, as well as corresponding polyspectra in the harmonic domain. Using these moments, we derive analytical expressions for the joint two-point probability distribution function (2PDF) for smoothed tSZ (y_s) and convergence (\kappa_s) maps. The presence of tomographic information allows us to study the evolution of higher order {\em mixed} tSZ-weak lensing statistics with redshift. We express the joint PDFs p_{\kappa y}(\kappa_s,y_s) in terms of individual one-point PDFs (p_{\kappa}(\kappa_s), p_y(y_s)) and the relevant bias functions…
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