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Related papers: Propagating beliefs in spin glass models

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Spin-glass systems are universal models for representing many-body phenomena in statistical physics and computer science. High quality solutions of NP-hard combinatorial optimization problems can be encoded into low energy states of…

Disordered Systems and Neural Networks · Physics 2020-01-14 Gavin S. Hartnett , Masoud Mohseni

In this talk I will review some of the recent applications of the replica theory to glasses. I will firstly describe the basic assumptions and I will show that they can be considered as a precise reformulations of old ideas. The relation of…

Disordered Systems and Neural Networks · Physics 2007-05-23 Giorgio Parisi

Spin-glasses are natural Gibbs distributions that have been studied in Theoretical CS for many decades. Recently, they have been gaining attention from the community as they emerge naturally in neural computation and learning, network…

Discrete Mathematics · Computer Science 2026-03-25 Charilaos Efthymiou , Kostas Zampetakis

After briefly describing the present status of the spin glass theory, we present a conjecture on the exact location of the multicritical point in the phase diagram of finite-dimensional spin glasses. The theory enables us to understand in a…

Disordered Systems and Neural Networks · Physics 2007-05-23 Hidetoshi Nishimori , Koujin Takeda , Tomohiro Sasamoto

Belief Propagation (BP) is an important message-passing algorithm for various reasoning tasks over graphical models, including solving the Constraint Optimization Problems (COPs). It has been shown that BP can achieve state-of-the-art…

Artificial Intelligence · Computer Science 2022-09-27 Yanchen Deng , Shufeng Kong , Caihua Liu , Bo An

While the Gibbs states of spin glass models have been noted to have an erratic dependence on temperature, one may expect the mean over the disorder to produce a continuously varying ``quenched state''. The assumption of such continuity in…

Statistical Mechanics · Physics 2015-06-25 M. Aizenman , P. Contucci

Belief Propagation (BP) is one of the most popular methods for inference in probabilistic graphical models. BP is guaranteed to return the correct answer for tree structures, but can be incorrect or non-convergent for loopy graphical…

Artificial Intelligence · Computer Science 2012-06-22 Siamak Ravanbakhsh , Chun-Nam Yu , Russell Greiner

A feedback vertex set (FVS) of an undirected graph contains vertices from every cycle of this graph. Constructing a FVS of sufficiently small cardinality is very difficult in the worst cases, but for random graphs this problem can be…

Statistical Mechanics · Physics 2016-09-28 Shao-Meng Qin , Ying Zeng , Hai-Jun Zhou

Infinite-range spin-glass models with Levy-distributed interactions show a spin-glass transition with similarities to both the Sherrington-Kirkpatrick model and to disordered spin systems on finite connectivity random graphs. Despite the…

Disordered Systems and Neural Networks · Physics 2009-11-13 K. Janzen , A. K. Hartmann , A. Engel

In this work, we explore various relevant aspects of the Smoothed Particle Hydrodynamics regarding Burger's equation. The stability, precision, and efficiency of the algorithm are investigated in terms of different implementations. In…

Computational Physics · Physics 2020-01-08 Chong Ye , Philipe Mota , Jin Li , Kai Lin , Wei-Liang Qian

We obtain, for the first time, an analytic theory of the forward stimulated Brillouin scattering instability of a spatially and temporally incoherent laser beam, that controls the transition between statistical equilibrium and…

Plasma Physics · Physics 2009-11-10 Pavel M. Lushnikov , Harvey A. Rose

Max-product Belief Propagation (BP) is a popular message-passing algorithm for computing a Maximum-A-Posteriori (MAP) assignment over a distribution represented by a Graphical Model (GM). It has been shown that BP can solve a number of…

Data Structures and Algorithms · Computer Science 2015-09-24 Sungsoo Ahn , Sejun Park , Michael Chertkov , Jinwoo Shin

We study the L\'evy spin-glass model with the replica and the cavity method. In this model each spin interacts through a finite number of strong bonds and an infinite number of weak bonds. This hybrid behaviour of L\'evy spin glasses…

Disordered Systems and Neural Networks · Physics 2010-01-29 I. Neri , F. L. Metz , D. Bollé

Spin-glass theory is one of the leading paradigms of complex physics and describes condensed matter, neural networks and biological systems, ultracold atoms, random photonics, and many other research fields. According to this theory,…

Disordered Systems and Neural Networks · Physics 2017-08-23 N. Ghofraniha , I. Viola , F. Di Maria , G. Barbarella , G. Gigli , L. Leuzzi , C. Conti

Within the replica approach to mean-field spin-glasses the transition from ergodic high-temperature behaviour to the glassy low-temperature phase is marked by the instability of the replica-symmetric saddle-point. For general spin-glass…

Disordered Systems and Neural Networks · Physics 2015-05-19 Katharina Janzen , Andreas Engel

We present a novel inference algorithm for arbitrary, binary, undirected graphs. Unlike loopy belief propagation, which iterates fixed point equations, we directly descend on the Bethe free energy. The algorithm consists of two phases,…

Artificial Intelligence · Computer Science 2013-01-14 Max Welling , Yee Whye Teh

The fermionic Ising spin glass models in a transverse field are investigated in a Grassmann path integral formalism. The Parisi's scheme of one-step replica symmetry breaking (RSB) is used within the static ansatz. This formalism has…

Strongly Correlated Electrons · Physics 2009-11-11 F. M. Zimmer , S. G. Magalhaes

A directed graph (digraph) is formed by vertices and arcs (directed edges) from one vertex to another. A feedback vertex set (FVS) is a set of vertices that contains at least one vertex of every directed cycle in this digraph. The directed…

Physics and Society · Physics 2016-08-03 Hai-Jun Zhou

In a $p$-spin interaction spherical spin-glass model both the spins and the couplings are allowed to change in the course of time. The spins are coupled to a heat bath with temperature $T$, while the coupling constants are coupled to a bath…

Disordered Systems and Neural Networks · Physics 2009-10-31 A. E. Allahverdyan , Th. M. Nieuwenhuizen , D. B. Saakian

Predicting the distribution of future states in a stochastic system, known as belief propagation, is fundamental to reasoning under uncertainty. However, nonlinear dynamics often make analytical belief propagation intractable, requiring…

Machine Learning · Computer Science 2025-09-22 Peter Amorese , Morteza Lahijanian