Bayesian ICA-based source separation of Cosmic Microwave Background by a discrete functional approximation

2010/11/17 by Wilson, Simon P., Yoon, Jiwon
#62-07 #85-08 #Applications (stat.AP) #Cosmology and Nongalactic Astrophysics (astro-ph.CO) #FOS: Computer and information sciences #FOS: Physical sciences

paper · doi:10.48550/arxiv.1011.4018

Abstract

A functional approximation to implement Bayesian source separation analysis is introduced and applied to separation of the Cosmic Microwave Background (CMB) using WMAP data. The approximation allows for tractable full-sky map reconstructions at the scale of both WMAP and Planck data and models the spatial smoothness of sources through a Gaussian Markov random field prior. It is orders of magnitude faster than the usual MCMC approaches. The performance and limitations of the approximation are also discussed.

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