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Comparing cosmic shear measures - Optimizing the Information content of cosmic shear data vectors

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arxiv 0708.4125 v1 pith:SEQXXCWP submitted 2007-08-30 astro-ph

Comparing cosmic shear measures - Optimizing the Information content of cosmic shear data vectors

classification astro-ph
keywords datavectorinformationcontentangularcomparedcontaminationcorrelation
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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We introduce an optimized data vector of cosmic shear measures (N). This data vector has high information content, is not sensitive against B-mode contamination and only shows small correlation between data points of different angular scales. We show that a data vector of the two-point correlation function (2PCF) in general contains more information on cosmological parameters compared to a data vector of the aperture mass dispersion. Reason for this is the fact that <M_ap^2> lacks the information of the convergence power spectrum (P_\kappa) on large angular scales, which is contained in the 2PCF data vector. Therefore we create a combined data vector N, which retains the advantages of <M_ap^2> and in addition is also sensitive to the large-scale information of P_\kappa. We compare the information content of the three data vectors by performing a detailed likelihood analysis and use ray-tracing simulations to derive the covariance matrices. In the last part of the paper we contaminate all data vectors with B-modes on small angular scales and examine their robustness against this contamination.The combined data vector strongly improves constraints on cosmological parameters compared to <M_ap^2>. Although, in case of a pure E-mode signal the information content of the 2PCF is higher, in the more realistic case where B-modes are present the 2PCF data vector is strongly contaminated and yields biased cosmological parameter estimates. N shows to be robust against this contamination. Furthermore the individual data points of N show a much smaller correlation compared to the 2PCF leading to an almost diagonal covariance matrix.

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