Analysis of two-point statistics of cosmic shear-III. Covariances of shear measures made easy

B Joachimi, P Schneider, T Eifler�- Astronomy & Astrophysics, 2008 - aanda.org
B Joachimi, P Schneider, T Eifler
Astronomy & Astrophysics, 2008aanda.org
Aims. In recent years cosmic shear, the weak gravitational lensing effect by the large-scale
structure of the Universe, has proven to be one of the observational pillars on which the
cosmological concordance model is founded. Several cosmic shear statistics have been
developed in order to analyze data from surveys. For the covariances of the prevalent
second-order measures we present simple and handy formulae, valid under the
assumptions of Gaussian density fluctuations and a simple survey geometry. We also�…
Aims
In recent years cosmic shear, the weak gravitational lensing effect by the large-scale structure of the Universe, has proven to be one of the observational pillars on which the cosmological concordance model is founded. Several cosmic shear statistics have been developed in order to analyze data from surveys. For the covariances of the prevalent second-order measures we present simple and handy formulae, valid under the assumptions of Gaussian density fluctuations and a simple survey geometry. We also formulate these results in the context of shear tomography, i.e. the inclusion of redshift information, and generalize them to arbitrary data field geometries.
Methods
We define estimators for the E- and B-mode projected power spectra and show them to be unbiased in the case of Gaussianity and a simple survey geometry. From the covariance of these estimators we demonstrate how to derive covariances of arbitrary combinations of second-order cosmic shear measures. We then recalculate the power spectrum covariance for general survey geometries and examine the bias thereby introduced on the estimators for exemplary configurations.
Results
Our results for the covariances are considerably simpler than and analytically shown to be equivalent to the real-space approach presented in the first paper of this series. We find good agreement with other numerical evaluations and confirm the general properties of the covariance matrices. The studies of the specific survey configurations suggest that our simplified covariances may be employed for realistic survey geometries to good approximation.
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