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research
Performance of internal Covariance Estimators for Cosmic Shear Correlation Functions
Authors
T. F. Eifler
O. Friedrich
D. Gruen
S. Seitz
Publication date
1 March 2016
Publisher
'Oxford University Press (OUP)'
Doi
Cite
View
on
arXiv
Abstract
Data re-sampling methods such as the delete-one jackknife are a common tool for estimating the covariance of large scale structure probes. In this paper we investigate the concepts of internal covariance estimation in the context of cosmic shear two-point statistics. We demonstrate how to use log-normal simulations of the convergence field and the corresponding shear field to carry out realistic tests of internal covariance estimators and find that most estimators such as jackknife or sub-sample covariance can reach a satisfactory compromise between bias and variance of the estimated covariance. In a forecast for the complete, 5-year DES survey we show that internally estimated covariance matrices can provide a large fraction of the true uncertainties on cosmological parameters in a 2D cosmic shear analysis. The volume inside contours of constant likelihood in the
Ω
m
\Omega_m
Ω
m
​
-
σ
8
\sigma_8
σ
8
​
plane as measured with internally estimated covariance matrices is on average
≳
85
%
\gtrsim 85\%
≳
85%
of the volume derived from the true covariance matrix. The uncertainty on the parameter combination
Σ
8
∼
σ
8
Ω
m
0.5
\Sigma_8 \sim \sigma_8 \Omega_m^{0.5}
Σ
8
​
∼
σ
8
​
Ω
m
0.5
​
derived from internally estimated covariances is
∼
90
%
\sim 90\%
∼
90%
of the true uncertainty.Comment: submitted to mnra
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