Numerical complexity of the joint nulled weak-lensing probability distribution function

TL;DR

This paper investigates how a nulling transformation in weak lensing surveys simplifies the numerical complexity of estimating joint probability distribution functions, enabling more accurate theoretical predictions of cosmic shear observables.

Contribution

It introduces a method to analyze the reduced numerical complexity of joint PDFs in nulled weak lensing data, facilitating first-principles predictions.

Findings

Reduced computational complexity for joint PDF estimation

Enhanced accuracy in theoretical predictions of lensing observables

Potential for improved analysis of tomographic cosmic shear data

Abstract

In the context of tomographic cosmic shear surveys, there exists a nulling transformation of weak lensing observations (also called BNT transform) that allows us to simplify the correlation structure of tomographic cosmic shear observations, as well as to build observables that depend only on a localised range of redshifts and thus independent from the low-redshift/small-scale modes. This procedure renders possible accurate, and from-first-principles, predictions of the convergence and aperture mass one-point distributions (PDF). We here explore other consequences of this transformation on the (reduced) numerical complexity of the estimation of the joint PDF between nulled bins and demonstrate how to use these results to make theoretical predictions.