Optimizing the recovery of Fisher information in the dark matter power spectrum

Abstract

We examine and combine different techniques that are known to increase the Fisher information content about the amplitude of the matter power spectrum, and propagate their impact on a baryonic acoustic oscillation (BAO) measurement. We compare a density reconstruction algorithm based on Zel'dovich displacement fields, a wavelet non-linearWiener filter, a direct Gaussianization of the probability distribution function of the wavelet function coefficients and the action of the last two techniques on the first one. From a series of 200 N-body simulations, we compute the Fisher information and quantify the recovery performance, both using dark matter particles and haloes. We find that the height of the Fisher information trans-linear plateau is generally increased by the various techniques, by up to an order of magnitude at k = 0.6 h Mpc-1; however, shot noise subtracted halo measurements exhibit a milder information recovery. When we perform a BAO measurement from these altered density fields, we find that the reconstruction technique is the only one that sharpens the peak; the two wavelet-based techniques in fact smear out the features, thus reducing the overall precision of the cosmological ladder. We examine in detail why this occurs even though their Fisher information increased. © 2013 The Authors Published by Oxford University Press on behalf of the Royal Astronomical Society.