Bayesian analysis of inflationary features in Planck and SDSS data

TL;DR

This paper uses Bayesian methods to analyze potential features in the primordial inflationary power spectrum, utilizing recent CMB and matter power spectrum data to assess their detectability and fit to observations.

Contribution

It introduces a Bayesian framework to evaluate localized inflationary features using combined Planck and SDSS data, comparing different potential models.

Findings

Oscill-1 potential fits CMB data better than LCDM.

Adding P(k) data weakens evidence for Oscill-1.

Standard LCDM model is favored when combining datasets.

Abstract

We perform a Bayesian analysis to study possible features in the primordial inflationary power spectrum of scalar perturbations. In particular, we analyse the possibility of detecting the imprint of these primordial features in the anisotropy temperature power spectrum of the Cosmic Microwave Background (CMB) and also in the matter power spectrum P (k). We use the most recent CMB data provided by the Planck Collaboration and P (k) measurements from the eleventh data release of the Sloan Digital Sky Survey. We focus our analysis on a class of potentials whose features are localised at different intervals of angular scales, corresponding to multipoles in the ranges 10 < l < 60 (Oscill-1) and 150 < l < 300 (Oscill-2). Our results show that one of the step-potentials (Oscill-1) provides a better fit to the CMB data than does the featureless LCDM scenario, with a moderate Bayesian evidence in favor of the former. Adding the P (k) data to the analysis weakens the evidence of the Oscill-1 potential relative to the standard model and strengthens the evidence of this latter scenario with respect to the Oscill-2 model.