Analysis of two-point statistics of cosmic shear: II. Optimizing the survey geometry

TL;DR

This paper investigates how survey geometry affects the accuracy of cosmological parameter estimation from cosmic shear data, using simulations and covariance analysis to optimize survey design.

Contribution

It introduces a method to optimize survey geometry for cosmic shear measurements by analyzing covariance matrices and Fisher information, improving parameter constraints.

Findings

Optimal survey consists of 10 patches with 30 images each.

Minimum variance bounds for _m, _8, and _Gamma are 0.17, 0.25, and 0.04.

Survey geometry significantly influences the precision of cosmological parameters.

Abstract

We present simulations of a cosmic shear survey and show how the survey geometry influences the accuracy of determination of cosmological parameters. We numerically calculate the full covariance matrices Cov of two-point statistics of cosmic shear, based on the expressions derived in the first paper of this series. The individual terms are compared for two survey geometries with large and small cosmic variance. We use analyses based on maximum likelihood of Cov and the Fisher information matrix in order to derive expected constraints on cosmological parameters. As an illustrative example, we simulate various survey geometries consisting of 300 individual fields of 13'x13' size, placed (semi-)randomly into patches which are assumed to be widely separated on the sky and therefore uncorrelated. Using the aperture mass statistics, the optimum survey consists of 10 patches with 30 images in each patch. If \Omega_m, \sigma_8 and \Gamma are supposed to be extracted from the data, the minimum variance bounds on these three parameters are 0.17, 0.25 and 0.04 respectively. These variances raise slightly when the initial power spectrum index n_s is also to be determined from the data. The cosmological constant is only poorly constrained.