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Replica symmetry breaking postulates that near optima of spin glass Hamiltonians have an ultrametric structure. Namely, near optima can be associated to leaves of a tree, and the Euclidean distance between them corresponds to the distance…

Probability · Mathematics 2022-06-22 Antonio Auffinger , Andrea Montanari , Eliran Subag

We present and solve the Replica Symmetric equations in the context of the Replica Cluster Variational Method for the 2D random bond Ising model (including the 2D Edwards-Anderson spin glass model). First we solve a linearized version of…

Disordered Systems and Neural Networks · Physics 2015-06-04 Alejandro Lage-Castellanos , Roberto Mulet , Federico Ricci-Tersenghi , Tommaso Rizzo

We investigate an extended +-J Ising spin glass model by using a gauge symmetry. This model has +-J1 interactions and +-J2 interactions. We show that a gauge symmetry is usable to study this model. The exact internal energy, the rigorous…

Disordered Systems and Neural Networks · Physics 2012-07-27 Chiaki Yamaguchi

Dilute dipolar Ising magnets remain a notoriously hard problem to tackle both analytically and numerically because of long-ranged interactions between spins as well as rare region effects. We study a new type of anisotropic dilute dipolar…

Disordered Systems and Neural Networks · Physics 2019-08-28 Tushar Kanti Bose , Roderich Moessner , Arnab Sen

The sample-to-sample fluctuations of the free energy in finite-dimensional Ising spin glasses are calculated, using the replica method, from higher order terms in the replica number $n$. It is shown that the Parisi symmetry breaking scheme…

Statistical Mechanics · Physics 2009-11-07 T. Aspelmeier , M. A. Moore

As spin glass materials have extremely slow dynamics, devious numerical methods are needed to study low-temperature states. A simple and fast optimization version of the classical Kasteleyn treatment of the Ising model is described and…

Disordered Systems and Neural Networks · Physics 2008-02-28 Creighton K. Thomas , A. Alan Middleton

Optimizing a high-dimensional non-convex function is, in general, computationally hard and many problems of this type are hard to solve even approximately. Complexity theory characterizes the optimal approximation ratios achievable in…

Statistical Mechanics · Physics 2020-09-25 Ahmed El Alaoui , Andrea Montanari

A sketch of the chapter appearing under the same heading in the book ``New Optimization Algorithms in Physics'' (A.K. Hartmann and H. Rieger, Eds.) is given. After a general introduction to spin glasses, important aspects of heuristic…

Disordered Systems and Neural Networks · Physics 2007-05-23 Olivier C. Martin

An efficient algorithm is developed to construct disconnectivity graphs by a random walk over basins of attraction. This algorithm can detect a large number of local minima, find energy barriers between them, and estimate local thermal…

Statistical Mechanics · Physics 2011-08-08 Qing Zhou

We devise a deterministic algorithm to efficiently sample high-quality solutions of certain spin-glass systems that encode hard optimization problems. We employ tensor networks to represent the Gibbs distribution of all possible…

Statistical Mechanics · Physics 2021-09-07 Marek M. Rams , Masoud Mohseni , Daniel Eppens , Konrad Jałowiecki , Bartłomiej Gardas

Thermal cycling is an heuristic optimization algorithm which consists of cyclically heating and quenching by Metropolis and local search procedures, respectively, where the amplitude slowly decreases. In recent years, it has been…

Disordered Systems and Neural Networks · Physics 2017-08-23 A. Mobius , K. H. Hoffmann , C. Schon

The recently proposed Hysteretic Optimization (HO) procedure is applied to the 1D Ising spin chain with long range interactions. To study its effectiveness, the quality of ground state energies found as a function of the distance dependence…

Soft Condensed Matter · Physics 2008-01-30 B. Goncalves , S. Boettcher

A spin glass is a diluted magnetic material in which the magnetic moments are randomly interacting, with a huge number of metastable states which prevent reaching equilibrium. Spin-glass models are conceptually simple, but require very…

Disordered Systems and Neural Networks · Physics 2023-03-03 Eric Vincent

Due to an extremely rugged structure of the free energy landscape, the determination of spin-glass ground states is among the hardest known optimization problems, found to be NP-hard in the most general case. Owing to the specific structure…

Disordered Systems and Neural Networks · Physics 2011-11-10 Martin Weigel

We consider $h$-stable local optima of Ising spin glass models, defined as spin configurations such that for nearly all of the spins, flipping their values results in increasing energy by at least a given amount $h$. Spins satisfying this…

Probability · Mathematics 2025-09-10 Yatin Dandi , David Gamarnik , Lenka Zdeborová

We introduce a hierarchical class of approximations of the random Ising spin glass in $d$ dimensions. The attention is focused on finite clusters of spins where the action of the rest of the system is properly taken into account. At the…

Disordered Systems and Neural Networks · Physics 2009-10-30 R. Baviera , M. Pasquini , M. Serva

We present a continuous nonlinear optimization model for the Spin Glass Problem (SGP), building on a classical result by Rosenberg (1972), which shows that for a class of multilinear polynomial problems the optimal values of the continuous…

Computational Physics · Physics 2025-12-08 Phil Duxbury , Carlile Lavor , Luiz Leduino de Salles-Neto

The \emph{Steiner tree} problem is one of the fundamental and classical problems in combinatorial optimization. In this paper, we study this problem in the $\mathcal{CONGESTED}$ $\mathcal{CLIQUE}$ model of distributed computing and present…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-07-31 Parikshit Saikia , Sushanta Karmakar

An approximate numerical approach to spin models is proposed, in which the original lattice is transformed into a tree. This method is applied to the Edwards-Anderson spin glass model in two and three dimensions. It captures the…

Disordered Systems and Neural Networks · Physics 2007-05-23 Naoki Kawashima

Many iterative and non-iterative methods have been developed for inverse problems associated with Ising models. Aiming to derive an accurate non-iterative method for the inverse problems, we employ the tree-reweighted approximation. Using…

Machine Learning · Statistics 2018-05-30 Takashi Sano