Information, Physics, and Computation (Oxford Graduate Texts) (英語) ハードカバー – 2009/3/27
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This book presents a unified approach to a rich and rapidly evolving research domain at the interface between statistical physics, theoretical computer science/discrete mathematics, and coding/information theory. It is accessible to graduate students and researchers without a specific training in any of these fields. The selected topics include spin glasses, error correcting codes, satisfiability, and are central to each field. The approach focuses on large random instances and adopts a common probabilistic formulation in terms of graphical models. It presents message passing algorithms like belief propagation and survey propagation, and their use in decoding and constraint satisfaction solving. It also explains analysis techniques like density evolution and the cavity method, and uses them to study phase transitions.
`Combines an exceptionally broad coverage of non-trivial problems with a treatment of sufficient depth [...] A very valuable and unique book.' ACC Coolen, King's College London
`There is a growing awareness within computer science that concepts from statistical physics and information theory can provide excellent tools to study computational methods and problems. This book, by world-renowned experts in the field, provides a lucid introduction to this exciting new interdisciplinary research area. ' Bart Selman, Cornell University
`No doubt a book of highest quality.' Heiko Rieger, Saarland University
Professor Marc Mezard CNRS Research Director at Université de Paris Sud and Professor at Ecole Polytechnique, France Marc Mezard received his PhD in 1984. He was hired in CNRS in 1981 and became research director in 1990 at Ecole Normale Supérieure. He joined the Université Paris Sud in 2001. He spent extensive periods in Rome University, in the KITP (Santa Barbara) and in MSRI (Berkeley). Author of about 150 publications, he has been awarded the silver medal of CNRS in 1990 and the Ampere price of the French academy of science in 1996. Dr Andrea Montanari Assistant Professor, Stanford University and CNRS France Andrea Montanari received a Laurea degree in Physics in 1997, and a Ph. D. in Theoretical Physics in 2001 (both from Scuola Normale Superiore in Pisa, Italy). He has been post-doctoral fellow at Laboratoire de Physique Théorique de l'Ecole Normale Supérieure (LPTENS), Paris, France, and the Mathematical Sciences Research Institute, Berkeley, USA. Since 2002 he is Chargé de Recherche (a permanent research position with Centre National de la Recherche Scientifique, CNRS) at LPTENS. In September 2006 he joined Stanford University as Assistant Professor in the Departments of Electrical Engineering and Statistics. In 2006 he was awarded the CNRS bronze medal for theoretical physics.
from very elementary material, assuming almost zero prior knowledge,
gives a comprehensive treatment of a full plate of concepts and ideas
in these three disciplines, and ends with modern coding theory and its
relationship with statistical mechanics. Personally, I have been using
this book for quite some time and it helped me a great deal. On the down
side, there is some mismatch, along the book, between the degree of
difficulty of the concepts being taught and the level of explanation and
the rigor behind it: There are some relatively simple notions and results
whose explanations are rather lengthy and detailed, whereas on the other
hand, more complicated ideas and results are sometimes explained very
briefly, leaving a lot to be desired. But in spite of this caveat, I still
recommend this book warmly.