WMAP 7 Constraints on Oscillations in the Primordial Power Spectrum

TL;DR

This paper uses WMAP 7 data to constrain oscillations in the primordial power spectrum, exploring models with initial state modifications and employing efficient computational techniques to improve existing constraints.

Contribution

It introduces a computationally efficient method to constrain oscillations in the primordial spectrum using WMAP 7 data, focusing on models with non-trivial initial states.

Findings

Certain frequencies improve fit over no-oscillation models

Constraints on oscillation amplitude and frequency are tightened

Method reduces computational time for spectral evaluations

Abstract

We use the WMAP 7 data to place constraints on oscillations supplementing an almost scale-invariant primordial power spectrum. Such oscillations are predicted by a variety of models, some of which amount to assuming there is some non-trivial choice of the vacuum state at the onset of inflation. In this paper we will explore data-driven constraints on two distinct models of initial state modifications. In both models the frequency, phase and amplitude are degrees of freedom of the theory for which the theoretical bounds are rather weak: both the amplitude and frequency have allowed values ranging over several orders of magnitude. This requires many computationally expensive evaluations of the model CMB spectra and their goodness-of-fit, even in a Markov Chain Monte Carlo (MCMC), normally the most efficient fitting method for such a problem. To search more efficiently we first run a densely spaced grid, with only 3 varying parameters; the frequency, the amplitude and the baryon density. We obtain the optimal frequency and run an MCMC at the best fit frequency, randomly varying all other relevant parameters. To reduce the computational time of each power spectrum computation, we adjust both comoving momentum integration and spline interpolation (in l) as a function of frequency and amplitude of the primordial power spectrum. Applying this to the WMAP 7 data allows us to improve existing constraints on the presence of oscillations. We confirm earlier findings that certain frequencies can improve the fitting over a model without oscillations. For those frequencies we compute the posterior probability, allowing us to put some constraints on the primordial parameter space of both models.