The Non-Linear Fisher Information content of cosmic shear surveys

TL;DR

This paper assesses the Fisher information in cosmic shear surveys, revealing how non-linear non-Gaussianities impact dark energy constraints, and introduces a new covariance estimation method with improved accuracy.

Contribution

It introduces a novel scheme for covariance matrix estimation in cosmic shear analysis, accounting for non-linear effects, with an unbiased estimator requiring fewer simulations.

Findings

Non-linear non-Gaussianity can reduce dark energy figure of merit by up to a factor of 4.

Realistic shot noise levels mitigate the non-Gaussian impact, reducing the effect to about 1.5 times.

The new covariance estimator improves accuracy by an order of magnitude with only twice the simulations.

Abstract

We quantify the Fisher information content of the cosmic shear survey two-point function as a function of noise and resolution. The two point information of dark matter saturates at the trans-linear scale. We investigate the impact of non-linear non-Gaussianity on the information content for lensing, which probes the same dark matter. To do so we heavily utilize N-body simulations in order to probe accurately the non-linear regime. While we find that even in a perfect survey, there is no clear saturation scale, we observe that non-linear growth induced non-Gaussianity could lead to a factor of ~4 reduction for the common Dark Energy figure of merit. This effect is however mitigated by realistic levels of shot noise and we find that for future surveys, the effect is closer to a factor of 1.5. To do so, we develop a new scheme to compute the relevant covariant matrix. It leads us to claim an unbiased estimator with an order of magnitude improvement in accuracy with only twice more simulations than previously used. Finally, we evaluate the error on the errors using bootstrap methods.