A self-contained guide to the CMB Gibbs sampler
arXiv:0905.3823
Abstract
We present a consistent self-contained and pedagogical review of the CMB Gibbs sampler, focusing on computational methods and code design. We provide an easy-to-use CMB Gibbs sampler named SLAVE developed in C++ using object-oriented design. While discussing why the need for a Gibbs sampler is evident and what the Gibbs sampler can be used for in a cosmological context, we review in detail the analytical expressions for the conditional probability densities and discuss the problems of galactic foreground removal and anisotropic noise. Having demonstrated that SLAVE is a working, usable CMB Gibbs sampler, we present the algorithm for white noise level estimation. We then give a short guide on operating SLAVE before introducing the post-processing utilities for obtaining the best-fit power spectrum using the Blackwell-Rao estimator.
11 pages,
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- Five-Year Wilkinson Microwave Anisotropy Probe (WMAP) Observations: Bayesian Estimation of CMB Polarization Maps
- Bayesian component separation and CMB estimation for the 5-year WMAP temperature data
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Cited by in corpus (4)
- Bayesian analysis of an anisotropic universe model: systematics and polarization
- Cosmo++: An Object-Oriented C++ Library for Cosmology
- Bayesian analysis of white noise levels in the 5-year WMAP data
- Imprints of a hemispherical power asymmetry in the seven-year WMAP data due to non-commutativity of space-time