Joint Bayesian separation and restoration of CMB from convolutional mixtures

Details Joint Bayesian separation and restoration of CMB from convolutional mixtures Joint Bayesian separation and restoration of CMB from convolutional mixtures

2011-01-07

arxiv.org/abs/1101.1397v1

Astronomy and Astrophysics

Astrophysics

Instrumentation and Methods for Astrophysics

11 pages, 6 figures. Submitted to MNRAS

Scientific paper

We propose a Bayesian approach to joint source separation and restoration for astrophysical diffuse sources. We constitute a prior statistical model for the source images by using their gradient maps. We assume a t-distribution for the gradient maps in different directions, because it is able to fit both smooth and sparse data. A Monte Carlo technique, called Langevin sampler, is used to estimate the source images and all the model parameters are estimated by using deterministic techniques.

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