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Zusatztext `No doubt a book of highest quality.'Heiko Rieger, Saarland University Informationen zum Autor 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. Klappentext A very active field of research is emerging at the frontier of statistical physics, theoretical computer science/discrete mathematics, and coding/information theory. This book sets up a common language and pool of concepts, accessible to students and researchers from each of these fields. Zusammenfassung A very active field of research is emerging at the frontier of statistical physics, theoretical computer science/discrete mathematics, and coding/information theory. This book sets up a common language and pool of concepts, accessible to students and researchers from each of these fields. Inhaltsverzeichnis 1: Introduction to Information Theory 2: Statistical physics and probability theory 3: Introduction to combinatorial optimization 4: Probabilistic toolbox 5: The Random Energy Model 6: Random Code Ensemble 7: Number partitioning 8: Introduction to replica theory 9: Factor graphs and graph ensembles 10: Satisfiability 11: Low-Density Parity-Check Codes 12: Spin glasses 13: Bridges: Inference and Monte Carlo 14: Belief propagation 15: Decoding with belief propagation 16: The assignment problem 17: Ising models on random graphs 18: Linear Boolean equations 19: The 1RSB cavity method 20: Random K-satisfiability 21: Glassy states in coding theory 22: An ongoing story ...
