A self-contained guide to the CMB Gibbs sampler

dc.creatorGroeneboom, Nicolaas E.
dc.date2009-05-23
dc.date.accessioned2026-07-07T13:17:48Z
dc.date.available2026-07-07T13:17:48Z
dc.descriptionWe 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.
dc.description11 pages,
dc.identifierhttps://arxiv.org/abs/0905.3823
dc.identifierhttp://arxiv.org/abs/0905.3823
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/231231
dc.subjectCosmology and Nongalactic Astrophysics
dc.titleA self-contained guide to the CMB Gibbs sampler
dc.typetext

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