Increasing the Fisher Information Content in the Matter Power Spectrum by Non-linear Wavelet Weiner Filtering

Abstract

We develop a purely mathematical tool to recover some of the information lost in the non-linear collapse of large-scale structure. From a set of 141 simulations of dark matter density fields, we construct a non-linear Weiner filter in order to separate Gaussian and non-Gaussian structure in wavelet space. We find that the non-Gaussian power is dominant at smaller scales, as expected from the theory of structure formation, while the Gaussian counterpart is damped by an order of magnitude on small scales. We find that it is possible to increase the Fisher information by a factor of three before reaching the translinear plateau, an effect comparable to other techniques like the linear reconstruction of the density field.

arXiv comment7 pages, 6 figures. Accepted for publication in The Astrophysical Journal

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Cited by in corpus (21)

• Power Spectrum Super-Sample Covariance
• High Performance P3M N-body code: CUBEP3M
• The Initial Conditions of the Universe from Constrained Simulations
• Joint analysis of cluster number counts and weak lensing power spectrum to correct for the super-sample covariance
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• Linearisation with Cosmological Perturbation Theory
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• Rejuvenating the Matter Power Spectrum III: The Cosmology Sensitivity of Gaussianized Power Spectra
• Sufficient observables for large scale structure in galaxy surveys
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• Dark Energy from the log-transformed convergence field
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• Simultaneous Dependence of Matter Clustering on Scale and Environment
• The effect of the linear term on the wavelet estimator of primordial non-Gaussianity
• The copula of the cosmological matter density field is non-Gaussian
• Perturbative Gaussianizing transforms for cosmological fields
• Optimizing the Recovery of Fisher Information in the Dark Matter Power Spectrum