Wavelet-Bayesian inference of cosmic strings embedded in the cosmic microwave background

Jason D. McEwen, S. M. Feeney, Hiranya V. Peiris, Yves Wiaux, C. Ringeval, F. R. Bouchet

Research output: Contribution to journalArticlepeer-review

20 Citations (Scopus)
57 Downloads (Pure)

Abstract

Cosmic strings are a well-motivated extension to the standard cosmological model and could induce a subdominant component in the anisotropies of the cosmic microwave background (CMB), in addition to the standard inflationary component. The detection of strings, while observationally challenging, would provide a direct probe of physics at very high-energy scales. We develop a framework for cosmic string inference from observations of the CMB made over the celestial sphere, performing a Bayesian analysis in wavelet space where the string-induced CMB component has distinct statistical properties to the standard inflationary component. Our wavelet-Bayesian framework provides a principled approach to compute the posterior distribution of the string tension Gμ and the Bayesian evidence ratio comparing the string model to the standard inflationary model. Furthermore, we present a technique to recover an estimate of any string-induced CMB map embedded in observational data. Using Planck-like simulations, we demonstrate the application of our framework and evaluate its performance. The method is sensitive to Gμ ~ 5 × 10-7 for Nambu-Goto string simulations that include an integrated Sachs-Wolfe contribution only and do not include any recombination effects, before any parameters of the analysis are optimized. The sensitivity of the method compares favourably with other techniques applied to the same simulations.

Original languageEnglish
Pages (from-to)4081-4098
Number of pages18
JournalMonthly Notices of the Royal Astronomical Society
Volume472
Issue number4
Early online date5 Sept 2017
DOIs
Publication statusPublished - 21 Dec 2017

Keywords

  • Cosmic background radiation
  • Cosmology: observations
  • Methods: data analysis
  • Methods: statistical

ASJC Scopus subject areas

  • Astronomy and Astrophysics
  • Space and Planetary Science

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