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Generalized Ising models, also known as cluster expansions, are an important tool in many areas of condensed-matter physics and materials science, as they are often used in the study of lattice thermodynamics, solid-solid phase transitions,…

Statistical Mechanics · Physics 2016-06-27 Wenxuan Huang , Daniil Kitchaev , Stephen Dacek , Ziqin Rong , Zhiwei Ding , Gerbrand Ceder

We consider the Hamiltonians of mean-field spin glasses, which are certain random functions $H_N$ defined on high-dimensional cubes or spheres in $\mathbb R^N$. The asymptotic maximum values of these functions were famously obtained by…

Disordered Systems and Neural Networks · Physics 2024-01-23 Mark Sellke

Scaling arguments and precise simulations are used to study the square lattice $\pm J$ Ising spin glass, a prototypical model for glassy systems. Droplet theory predicts, and our numerical results show, entropically-stabilized long range…

Disordered Systems and Neural Networks · Physics 2011-07-21 Creighton K. Thomas , David A. Huse , A. Alan Middleton

We present a massive equilibrium simulation of the three-dimensional Ising spin glass at low temperatures. The Janus special-purpose computer has allowed us to equilibrate, using parallel tempering, L=32 lattices down to T=0.64 Tc. We…

In this paper, we extend the full replica symmetry breaking scheme to the Ising spin glass on a random regular graph. We propose a new martingale approach, that overcomes the limits of the Parisi-M\'ezard cavity method, providing a…

Statistical Mechanics · Physics 2018-09-25 Francesco Concetti

The inverse Ising problem seeks to reconstruct the parameters of an Ising Hamiltonian on the basis of spin configurations sampled from the Boltzmann measure. Over the last decade, many applications of the inverse Ising problem have arisen,…

Disordered Systems and Neural Networks · Physics 2017-09-13 Johannes Berg

We present an algorithm for finding ground states of two dimensional spin glass systems based on ideas from matrix product states in quantum information theory. The algorithm works directly at zero temperature and defines an approximate…

Disordered Systems and Neural Networks · Physics 2009-11-13 M. B. Hastings

We introduce a simple two-dimensional spin model with short-range interactions which shows glassy behavior despite a Hamiltonian which is completely homogeneous and possesses no randomness. We solve exactly for both the static partition…

Statistical Mechanics · Physics 2009-10-30 M. E. J. Newman , Cristopher Moore

In this work, we theoretically demonstrate that a strong enhancement of the Magnetocaloric Effect is achieved in geometrically frustrated cluster spin-glass systems just above the freezing temperature. We consider a network of clusters…

Disordered Systems and Neural Networks · Physics 2023-05-24 F. M. Zimmer , R. Mourao , M. Schmidt , M. A. Tumelero , S. G. Magalhaes

Glassy behavior is one of the main open problems in condensed matter physics. In this thesis, we approach the problem by studying spin-glasses and colloids, using several complementary strategies. From the point of view of model building,…

Disordered Systems and Neural Networks · Physics 2013-09-10 B. Seoane

We introduce efficient algorithms for approximate sampling from symmetric Gibbs distributions on the sparse random (hyper)graph. The examples we consider include (but are not restricted to) important distributions on spin systems and…

Discrete Mathematics · Computer Science 2024-03-20 Charilaos Efthymiou

Spin Glasses (SG) are paradigmatic models for physical, computer science, biological and social systems. The problem of studying the dynamics for SG models is NP hard, i.e., no algorithm solves it in polynomial time. Here we implement the…

Disordered Systems and Neural Networks · Physics 2021-07-14 M. Leonetti , E. Hörmann , L. Leuzzi , G. Parisi , G. Ruocco

We study the classical 1D Heisenberg spin glasses. Based on the Hamilton equations we obtained the system of recurrence equations which allows to perform node-by-node calculations of a spin-chain. It is shown that calculations from first…

Disordered Systems and Neural Networks · Physics 2015-12-15 A. S. Gevorkyan , V. V. Sahakyan

We investigate the performance of the recently proposed stationary Fokker-Planck sampling method considering a combinatorial optimization problem from statistical physics. The algorithmic procedure relies upon the numerical solution of a…

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

We introduce an algorithm to generate (not solve) spin-glass instances with planted solutions of arbitrary size and structure. First, a set of small problem patches with open boundaries is solved either exactly or with a heuristic, and then…

Disordered Systems and Neural Networks · Physics 2017-08-31 Wenlong Wang , Salvatore Mandrà , Helmut G. Katzgraber

We consider the task of learning Ising models when the signs of different random variables are flipped independently with possibly unequal, unknown probabilities. In this paper, we focus on the problem of robust estimation of…

Machine Learning · Statistics 2020-06-11 Ashish Katiyar , Vatsal Shah , Constantine Caramanis

The monography considers the problem of constructing a Hamiltonian cycle in a complete graph. A rule for constructing a Hamiltonian cycle based on isometric cycles of a graph is established. An algorithm for constructing a Hamiltonian cycle…

Combinatorics · Mathematics 2024-09-19 Sergey Kurapov , Maxim Davidovsky , Svetlana Polyuga

Spin glasses are fundamental probability distributions at the core of statistical physics, the theory of average-case computational complexity, and modern high-dimensional statistical inference. In the mean-field setting, we design…

Data Structures and Algorithms · Computer Science 2025-11-07 Ferenc Bencs , Brice Huang , Daniel Z. Lee , Kuikui Liu , Guus Regts

The full replica symmetry breaking free energy of the Ising spin glass on random regular graphs is given by the solutions of two auxiliary variational problems inside a global (physical) variational problem on the order parameter. In this…

Statistical Mechanics · Physics 2019-08-13 Francesco Concetti

Zeros of the $n$th moment of the partition function $[Z^n]$ are investigated in a vanishing temperature limit $\beta \to \infty$, $n \to 0$ keeping $y=\beta n \sim O(1)$. In this limit, the moment parameterized by $y$ characterizes the…

Disordered Systems and Neural Networks · Physics 2009-11-13 Tomoyuki Obuchi , Yoshiyuki Kabashima , Hidetoshi Nishimori