The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
Information, Physics, and Computation
Abstract
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. The topics which have been selected, including spin glasses, error correcting codes, satisfiability, are central to each field. The approach focuses on the limit of large random instances, adopting a common 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 derive phase diagrams and study phase transitions.
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Cites
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Cited by
Ising formulations of many NP problems
Lucas, A. (2014) · Frontiers in Physics · doi:10.3389/fphy.2014.00005 · Cited by 2,512
Identification of direct residue contacts in protein–protein interaction by message passing
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Simulating Chemistry Using Quantum Computers
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Opportunities and challenges for quantum-assisted machine learning in near-term quantum computers
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Quantum critical dynamics in a 5,000-qubit programmable spin glass
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The overlap gap property: A topological barrier to optimizing over random structures
Gamarnik, D. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2108492118 · Cited by 103
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On the emerging potential of quantum annealing hardware for combinatorial optimization
Tasseff, B., Albash, T., Morrell, Z., Vuffray, M., Lokhov, A. Y., Misra, S., & Coffrin, C. (2024) · Journal of Heuristics · doi:10.1007/s10732-024-09530-5 · Cited by 42
Anergy in self-directed B lymphocytes: A statistical mechanics perspective
Agliari, E., Barra, A., Del Ferraro, G., Guerra, F., & Tantari, D. (2015) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2014.05.006 · Cited by 34
Tensor networks contraction and the belief propagation algorithm
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Relevance in the Renormalization Group and in Information Theory
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Metadata
- Authors
- Mézard, M., & Montanari, A.
- Publisher
- Oxford University PressOxford
- Published
- 2009-01-22
- OpenAlex
- W2566505556
- Cited by
- 1,913
- References
- 8
- FWCI
- 74.20
- Type
- book
- Language
- en
- Open access
- closed
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