The replica symmetric phase of random constraint satisfaction problems

Author:

Coja-Oghlan Amin,Kapetanopoulos Tobias,Müller Noela

Abstract

AbstarctRandom constraint satisfaction problems play an important role in computer science and combinatorics. For example, they provide challenging benchmark examples for algorithms, and they have been harnessed in probabilistic constructions of combinatorial structures with peculiar features. In an important contribution (Krzakala et al. 2007, Proc. Nat. Acad. Sci.), physicists made several predictions on the precise location and nature of phase transitions in random constraint satisfaction problems. Specifically, they predicted that their satisfiability thresholds are quite generally preceded by several other thresholds that have a substantial impact both combinatorially and computationally. These include the condensation phase transition, where long-range correlations between variables emerge, and the reconstruction threshold. In this paper we prove these physics predictions for a broad class of random constraint satisfaction problems. Additionally, we obtain contiguity results that have implications for Bayesian inference tasks, a subject that has received a great deal of interest recently (e.g. Banks et al. 2016, Proc. 29th COLT).

Publisher

Cambridge University Press (CUP)

Subject

Applied Mathematics,Computational Theory and Mathematics,Statistics and Probability,Theoretical Computer Science

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Local Geometry of NAE-SAT Solutions in the Condensation Regime;Proceedings of the 56th Annual ACM Symposium on Theory of Computing;2024-06-10

2. Polarised random -SAT;Combinatorics, Probability and Computing;2023-07-20

3. Finite-size scaling, phase coexistence, and algorithms for the random cluster model on random graphs;Annales de l'Institut Henri Poincaré, Probabilités et Statistiques;2023-05-01

4. Strong Replica Symmetry in High-Dimensional Optimal Bayesian Inference;Communications in Mathematical Physics;2022-04-09

5. The number of satisfying assignments of random 2‐SAT formulas;Random Structures & Algorithms;2021-01-17

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