4.7 Article

WMAP7 constraints on oscillations in the primordial power spectrum

Journal

MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
Volume 421, Issue 1, Pages 369-380

Publisher

OXFORD UNIV PRESS
DOI: 10.1111/j.1365-2966.2011.20311.x

Keywords

methods: data analysis; cosmic background radiation; inflation; cosmology: theory; early Universe

Funding

  1. Netherlands Organization for Scientific Research (NWO) [021.001.040]
  2. Foundation of Fundamental Research of Matter (FOM) [06PR2510]

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We use the 7-year Wilkinson Microwave Anisotropy Probe (WMAP7) 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 that 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 cosmic microwave background (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 three varying parameters: the frequency, the amplitude and the baryon density. We obtain the optimal frequency and run an MCMC at the best-fitting 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 WMAP7 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.

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