Description

Book Synopsis
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.

Trade 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

Table of Contents
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

Information Physics and Computation

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    A Hardback by Marc Mézard, Andrea Montanari

    £92.42

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    Order before 4pm today for delivery by Wed 25 Nov 2026.

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      Book details

      Published 22 January 2009
      ISBN-13 9780198570837
      978-0198570837
      ISBN-10 019857083X

      Description

      Book Synopsis
      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.

      Trade 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

      Table of Contents
      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

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