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A powerful existing technique for evaluating statistical mechanical quantities in two-dimensional Ising models is based on constructing a matrix representing the nearest neighbor spin couplings and then evaluating the Pfaffian of the…

Disordered Systems and Neural Networks · Physics 2013-04-16 Creighton K. Thomas , A. Alan Middleton

We introduce an exact algorithm for the computation of spin correlation functions for the two dimensional +/-J Ising spin glass in the ground state. Unlike with the transfer matrix method, there is no particular restriction on the shape of…

Disordered Systems and Neural Networks · Physics 2007-05-23 J. Poulter , J. A. Blackman

Models of interacting complex systems provide the fundamental statistical physics reference frame for the study and the understanding of associative memories, machine learning, and the dynamics of neural networks. On the other hand,…

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

The photonic Ising machine is a new paradigm of optical computing that takes advantage of the unique properties of light wave propagation, parallel processing, and low-loss transmission. Thus, the process of solving combinatorial…

Emerging Technologies · Computer Science 2025-04-08 Jiayi Ouyang , Yuxuan Liao , Zhiyao Ma , Deyang Kong , Xue Feng , Xiang Zhang , Xiaowen Dong , Kaiyu Cui , Fang Liu , Wei Zhang , Yidong Huang

Solving intractable mathematical problems in simulators composed of atoms, ions, photons or electrons has recently emerged as a subject of intense interest. Here we extend this concept to phonons that are localised in spectrally pure…

Mesoscale and Nanoscale Physics · Physics 2016-06-29 I. Mahboob , H. Yamaguchi

In this work, we proposed and experimentally demonstrated a photonic simulator for XY models, which is a typical kind of classical spin models. By encoding the XY spins on the phase term of the input light field, the corresponding XY…

We propose and demonstrate a nonlinear optics approach to emulate Ising machines containing up to a million spins and with tailored two and four-body interactions with all-to-all connections. It uses a spatial light modulator to encode and…

Optics · Physics 2020-10-21 Santosh Kumar , He Zhang , Yu-Ping Huang

After developing an appropriate iteration procedure for the determination of the parameters, the method of simulated tempering has been successfully applied to the 2D Ising spin glass. The reduction of the slowing down is comparable to that…

Condensed Matter · Physics 2009-10-22 Werner Kerler , Peter Rehberg

We explore the potential of spatial-photonic Ising machines (SPIMs) to address computationally intensive Ising problems that employ low-rank and circulant coupling matrices. Our results indicate that the performance of SPIMs is critically…

Spin systems with frustration and disorder are notoriously difficult to study both analytically and numerically. While the simulation of ferromagnetic statistical mechanical models benefits greatly from cluster algorithms, these accelerated…

Disordered Systems and Neural Networks · Physics 2015-08-18 Zheng Zhu , Andrew J. Ochoa , Helmut G. Katzgraber

We introduce a novel framework for simulating spin models using differentiable programming, an approach that leverages the advancements in machine learning and computational efficiency. We focus on three distinct spin systems: the Ising…

Statistical Mechanics · Physics 2024-05-28 Tiago de Souza Farias , Vitor Vaz Schultz , José Carlos Merino Mombach , Jonas Maziero

From condensed matter to quantum chromodynamics, multidimensional spins are a fundamental paradigm, with a pivotal role in combinatorial optimization and machine learning. Machines formed by coupled parametric oscillators can simulate spin…

Optics · Physics 2022-11-29 Marcello Calvanese Strinati , Claudio Conti

Computing the ground state of Ising spin-glass models with p-spin interactions is, in general, an NP-hard problem. In this work we show that unlike in the case of the standard Ising spin glass with two-spin interactions, computing ground…

Disordered Systems and Neural Networks · Physics 2015-03-17 Creighton K. Thomas , Helmut G. Katzgraber

A promising paradigm of quantum computing for achieving practical quantum advantages is quantum annealing or quantum approximate optimization algorithm, where the classical problems are encoded in Ising interactions. However, it is…

Quantum Physics · Physics 2025-06-25 Yao Lu , Wentao Chen , Shuaining Zhang , Kuan Zhang , Jialiang Zhang , Jing-Ning Zhang , Kihwan Kim

Spin glass systems as lattices of disordered magnets with random interactions have important implications within the theory of magnetization and applications to a wide-range of hard combinatorial optimization problems. Nevertheless, despite…

Disordered Systems and Neural Networks · Physics 2025-10-28 Fredrik Hasselgren , Max O. Al-Hasso , Amy Searle , Joseph Tindall , Marko von der Leyen

The need for solving optimization problems is prevalent in a wide range of physical applications, including neuroscience, network design, biological systems, socio-economics, and chemical reactions. Many of these are classified as…

A sampling algorithm is presented that generates spin glass configurations of the 2D Edwards-Anderson Ising spin glass at finite temperature, with probabilities proportional to their Boltzmann weights. Such an algorithm overcomes the slow…

Disordered Systems and Neural Networks · Physics 2009-10-30 Creighton K. Thomas , A. Alan Middleton

The ferromagnetic Ising model on an $n\times n$ square lattice region $\Lambda$ with mixed boundary conditions can exhibit a phase transition as temperature varies. For this spin system, if we fix the spins on the top and bottom sides of…

Discrete Mathematics · Computer Science 2026-05-26 David Gillman , Dana Randall

Ising models with pairwise interactions are the least structured, or maximum-entropy, probability distributions that exactly reproduce measured pairwise correlations between spins. Here we use this equivalence to construct Ising models that…

Neurons and Cognition · Quantitative Biology 2009-12-31 Gasper Tkacik , Elad Schneidman , Michael J. Berry , William Bialek