A roadmap to cosmological parameter analysis with third-order shear statistics III: Efficient estimation of third-order shear correlation functions and an application to the KiDS-1000 data

TL;DR

This paper introduces an efficient method for estimating third-order shear correlation functions in weak lensing data, enabling practical analysis of higher-order statistics in large surveys like KiDS-1000.

Contribution

We develop and validate a multipole-based estimator for third-order shear statistics that is 100-1000 times faster than previous methods, facilitating analysis in upcoming surveys.

Findings

Validated estimator on mock catalogs shows high accuracy.

Detected significant third-order aperture mass signal in KiDS-1000 data.

Speedup enables practical third-order shear analysis in future surveys.

Abstract

Third-order lensing statistics contain a wealth of cosmological information that is not captured by second-order statistics. However, the computational effort for estimating such statistics on forthcoming stage IV surveys is prohibitively expensive. We derive and validate an efficient estimation procedure for the three-point correlation function (3PCF) of polar fields such as weak lensing shear. We then use our approach to measure the shear 3PCF and the third-order aperture mass statistics on the KiDS-1000 survey. We construct an efficient estimator for third-order shear statistics which builds on the multipole decomposition of the 3PCF. We then validate our estimator on mock ellipticity catalogs obtained from $N$-body simulations. Finally, we apply our estimator to the KiDS-1000 data and present a measurement of the third-order aperture statistics in a tomographic setup. Our estimator provides a speedup of a factor of $\sim$ 100-1000 compared to the state-of-the-art estimation procedures. It is also able to provide accurate measurements for squeezed and folded triangle configurations without additional computational effort. We report a significant detection of the tomographic third-order aperture mass statistics in the KiDS-1000 data $(\mathrm{S/N}=6.69)$. Our estimator will make it computationally feasible to measure third-order shear statistics in forthcoming stage IV surveys. Furthermore, it can be used to construct empirical covariance matrices for such statistics.