Information, Physics, and Computation

Information, Physics, and Computation book cover

Information, Physics, and Computation

Author(s): Marc Mézard (Author), Andrea Montanari (Author)

  • Publisher: OUP Oxford
  • Publication Date: 22 Jan. 2009
  • Edition: 1st
  • Language: English
  • Print length: 584 pages
  • ISBN-10: 019857083X
  • ISBN-13: 9780198570837

Book Description

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.

Editorial Reviews

Review

`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

Book Description

This book sets up a common language and pool of concepts, accessible to students and researchers from statistical physics, theoretical computer science/discrete mathematics, and coding/information theory.

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