Revue de presse
This book is an excellent graduate-level text on the amazing connections between modern error-correcting codes (information theory), spin glass systems (condensed matter physics), and satisfiability problems (computational complexity). [...] I would expect any researcher working near the intersection of information theory, statistical physics and combinatorial optimization to find this book to be a highly-valued resource. (Mathematical Reviews
Information, Physics, and Computation is self-contained and should be accessible to any graduate student with a good background in probability theory and analysis.  Information, Physics, and Computation stimulates that cross-disciplinary dialog, which is always desirable because from it, new perspectives emerge. (Physics Today
Présentation de l'éditeur
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.