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Title: Bayesian analysis of the power spectrum of the cosmic microwave background
Authors: Jewell, Jeffrey B.
Eriksen, H. K.
O'Dwyer, I. J.
Wandelt, B. D.
Keywords: methods statistical
Bayesian inference
power spectrum
Gibbs sampling
Issue Date: 21-Apr-2005
Publisher: Pasadena, CA : Jet Propulsion Laboratory, National Aeronautics and Space Administration, 2004.
Citation: Society for Industrial and Applied Mathematics (SIAM) International Conference on Data Mining, Newport Beach, California, April 21, 2005.
Abstract: There is a wealth of cosmological information encoded in the spatial power spectrum of temperature anisotropies of the cosmic microwave background. The sky, when viewed in the microwave, is very uniform, with a nearly perfect blackbody spectrum at 2.7 degrees. Very small amplitude brightness fluctuations (to one part in a million!!) trace small density perturbations in the early universe (roughly 300,000 years after the Big Bang), which later grow through gravitational instability to the large-scale structure seen in redshift surveys... In this talk, I will discuss a Bayesian formulation of this problem; discuss a Gibbs sampling approach to numerically sampling from the Bayesian posterior, and the application of this approach to the first-year data from the Wilkinson Microwave Anisotropy Probe. I will also comment on recent algorithmic developments for this approach to be tractable for the even more massive data set to be returned from the Planck satellite.
Appears in Collections:JPL TRS 1992+

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