Fast estimation of aperture mass statistics II: Detectability of higher order statistics in current and future surveys

TL;DR

This paper introduces a direct estimator method for aperture mass statistics in weak lensing data, capable of efficiently retrieving higher order statistics up to tenth order, and demonstrates its effectiveness on mock surveys, including real-world simulations.

Contribution

It extends the direct estimator approach to arbitrary order and multiscale aperture mass statistics, enabling detection of higher order clustering in current and future surveys.

Findings

Validates the method on Gaussian mock surveys up to 10th order.

Demonstrates detection of up to fourth order clustering in realistic mock catalogs.

Applicable to large-scale surveys like Euclid and Rubin Telescope.

Abstract

We explore an alternative method to the usual shear correlation function approach for the estimation of aperture mass statistics in weak lensing survey data. Our approach builds on the direct estimator method. In this paper, we extend our analysis to statistics of arbitrary order and to the multiscale aperture mass statistics. We show that there always exists a linear order algorithm to retrieve any of these generalised aperture mass statistics from shape catalogs when the direct estimator approach is adopted. We validate our approach through application to a large number of Gaussian mock lensing surveys where the true answer is known and we do this up to 10th order statistics. We then apply our estimators to an ensemble of real-world mock catalogs obtained from N-body simulations - the SLICS mocks, and show that one can expect to retrieve detections of higher order clustering up to fourth order in a KiDS-1000 like survey. We expect that these methods will be of most utility for future wide-field surveys like Euclid and the Rubin Telescope.