Information Content in the Angular Power Spectrum of Weak Lensing: Wavelet Method

Abstract

We quantify the performance of a non-linear Wiener filter, constructed in wavelet space, at recovering some of the Fisher information that was lost in the weak lensing convergence field. The proposed method consists in a separation of the original field into the sum of a Gaussian and a non-Gaussian contribution. After filtering an ensemble of such fields, which are obtained from $N$-body simulations, we find that we can recapture about four times more Fisher information, an effect that can potentially improve by a significant amount the constraining power of weak lensing surveys on cosmological parameters, including the dark energy equation of state $\omega$. We compare this performance with that of the logarithmic mapping and find that the wavelet method can recover up to three times more information.

10 pages, 6 figures. Accepted by MNRAS

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Cited by in corpus (9)

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• Increasing Fisher Information by Moving-Mesh Reconstruction
• Nonlinear $E$-mode clustering in Lagrangian space
• Enhancing the Cosmic Shear Power Spectrum
• The effect of the linear term on the wavelet estimator of primordial non-Gaussianity
• The Weak Lensing Peak Statistics in the Mocks by the inverse-Gaussianization Method
• Optimizing the Recovery of Fisher Information in the Dark Matter Power Spectrum