Bayesian Methods in Cosmology

Michael P. Hobson

ISBN 10: 0521887941 / ISBN 13: 9780521887946

Published by Cambridge University Press, 2010

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Synopsis:

In recent years cosmologists have advanced from largely qualitative models of the Universe to precision modelling using Bayesian methods, in order to determine the properties of the Universe to high accuracy. This timely book is the only comprehensive introduction to the use of Bayesian methods in cosmological studies, and is an essential reference for graduate students and researchers in cosmology, astrophysics and applied statistics. The first part of the book focuses on methodology, setting the basic foundations and giving a detailed description of techniques. It covers topics including the estimation of parameters, Bayesian model comparison, and separation of signals. The second part explores a diverse range of applications, from the detection of astronomical sources (including through gravitational waves), to cosmic microwave background analysis and the quantification and classification of galaxy properties. Contributions from 24 highly regarded cosmologists and statisticians make this an authoritative guide to the subject.

About the Authors: M. P. Hobson is Reader in Astrophysics and Cosmology at the Cavendish Laboratory, University of Cambridge, where he researches theoretical and observational cosmology, Bayesian statistical methods, gravitation and theoretical optics.

Andrew H. Jaffe is Professor of Astrophysics and Cosmology at Imperial College and a member of the Planck Surveyor Satellite collaboration, which will create the highest-resolution and most sensitive maps of the CMB ever produced.

Andrew R. Liddle is Professor of Astrophysics at the University of Sussex. He is the author of over 150 journal articles and four books on cosmology, covering topics from early Universe theory to modelling astrophysical data.

Pia Mukherjee is a Postdoctoral Researcher in the Astronomy Centre at the University of Sussex, specialising in constraining cosmological models, including dark energy models, from observational data.

David Parkinson is a Postdoctoral Research Fellow in the Astronomy Centre at the University of Sussex, working in the areas of cosmology and the early Universe.

Bibliographic Details

Title: Bayesian Methods in Cosmology
Publisher: Cambridge University Press
Publication Date: 2010
Binding: Hardback
Condition: New