A roadmap to cosmological parameter analysis with third-order shear statistics II: Analytic covariance estimate

TL;DR

This paper develops and validates an analytic covariance model for third-order weak lensing aperture statistics, enabling accurate cosmological parameter analysis from stage III surveys.

Contribution

It introduces a new analytic covariance model for third-order aperture statistics validated against simulations, improving precision in cosmological analyses.

Findings

Model agrees within 3% with simulations for key parameters.

Covariance includes finite-field terms not scaling with survey area.

Model applicable for stage III survey data analysis.

Abstract

Third-order weak lensing statistics are a promising tool for cosmological analyses since they extract cosmological information in the non-Gaussianity of the cosmic large-scale structure. However, such analyses require precise and accurate models for the covariance. In this second paper of a series on third-order weak lensing statistics, we derive and validate an analytic model for the covariance of the third-order aperture statistics $\langle M_\mathrm{ap}^3\rangle$. We derive the covariance model from a real-space estimator for $\langle M_\mathrm{ap}^3\rangle$. We validate the model by comparing it to estimates from simulated Gaussian random fields (GRF) and two sets of N-body simulations. Finally, we perform mock cosmological analyses with the model covariance and the simulation estimate to compare the resulting parameter constraints. We find good agreement between the model and the simulations, both for the GRF and the $N$-body simulations. The figure-of-merit in the $S_8$-$\Omega_\mathrm{m}$ plane from our covariance model is within 3\% of the one obtained from the simulated covariances. We also show that our model, which is based on an estimator using convergence maps, can be used to obtain upper and lower bounds for the covariance of an estimator based on three-point shear correlation functions. This second estimator is required for realistic survey data. In our derivation, we find that the $\langle M_\mathrm{ap}^3\rangle$ covariance cannot be obtained from the bispectrum covariance and that it includes several `finite-field terms' that do not scale with the inverse survey area. Our covariance model is sufficiently accurate for analysing stage III surveys. Covariances for statistics in Fourier space cannot always be straightforwardly converted into covariance for real-space statistics. The modelling code is available at https://github.com/sheydenreich/threepoint/releases/ .