4.7 Article

Analysis of non-Gaussian cosmic microwave background maps based on the N-pdf. Application to Wilkinson Microwave Anisotropy Probe data

期刊

出版社

OXFORD UNIV PRESS
DOI: 10.1111/j.1365-2966.2009.14974.x

关键词

methods: data analysis; methods: statistical; cosmic microwave background; cosmology: observations

资金

  1. Spanish Ministerio de Ciencia e Innovacion [AYA2007-68058-C03-02]
  2. Spanish MEC
  3. CNR
  4. ISTI in Pisa
  5. NASA Office of Space Science

向作者/读者索取更多资源

We present a new method based on the N-point probability distribution function (N-pdf) to study non-Gaussianity in cosmic microwave background maps. Likelihood and Bayesian estimation are applied to a local non-linear perturbed model up to third order, characterized by a linear term which is described by a Gaussian N-pdf, and a second- and third-order terms which are proportional to the square and the cube of the linear one. We also explore a set of model selection techniques (the Akaike and the Bayesian information criteria, the minimum description length, the Bayesian evidence and the generalized likelihood ratio test) and their application to decide whether a given data set is better described by the proposed local non-Gaussian model, rather than by the standard Gaussian temperature distribution. As an application, we consider the analysis of the Wilkinson Microwave Anisotropy Probe 5-year data at a resolution of approximate to 2 degrees. At this angular scale (the Sachs-Wolfe regime), the non-Gaussian description proposed in this work defaults (under certain conditions) to an approximative local form of the weak non-linear coupling inflationary model previously addressed in the literature. For this particular case, we obtain an estimation for the non-linear coupling parameter of -94 < f(NL) < 154 at 95 per cent confidence level. Equally, model selection criteria also indicate that the Gaussian hypothesis is favoured against the particular local non-Gaussian model proposed in this work. This result is in agreement with previous findings obtained for equivalent non-Gaussian models and with different non-Gaussian estimators. However, our estimator based on the N-pdf is more efficient than previous estimators and, therefore, provides tighter constraints on the coupling parameter at degree scale.

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