Maximum Entropy deconvolution of Primordial Power Spectrum

Abstract

It is well known that CMB temperature anisotropies and polarization can be used to probe the metric perturbations in the early universe. Presently, there exist neither any observational detection of tensor modes of primordial metric perturbations nor of primordial non-Gaussianity. In such a scenario, primordial power spectrum of scalar metric perturbations is the only correlation function of metric perturbations (presumably generated during inflation) whose effects can be directly probed through various observations. To explore the possibility of any deviations from the simplest picture of the era of cosmic inflation in the early universe, it thus becomes extremely important to uncover the amplitude and shape of this (only available) correlation sufficiently well. In the present work, we attempt to reconstruct the primordial power spectrum of scalar metric perturbations using the binned (uncorrelated) CMB temperature anisotropies data using the Maximum Entropy Method (MEM) to solve the corresponding inverse problem. Our analysis shows that, given the current CMB data, there are no convincing reasons to believe that the primordial power spectrum of scalar metric perturbations has any significant features.

24 Pages, 13 Figures and 1 Table, Comments Welcome

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• Dark Radiation and Inflationary Freedom after Planck 2015
• Inflationary Freedom and Cosmological Neutrino Constraints
• Joint Planck and WMAP Assessment of Low CMB Multipoles
• Light Sterile Neutrinos and Inflationary Freedom
• PRISM: Sparse Recovery of the Primordial Power Spectrum
• CMB anomalies and the effects of local features of the inflaton potential
• Effects of local features of the inflaton potential on the spectrum and bispectrum of primordial perturbations
• Low-$\ell$ power suppression in punctuated inflation
• Bayesian inference methodology for Primordial Power Spectrum reconstructions from Large Scale Structure
• J-PAS: forecast on the primordial power spectrum reconstruction