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Dynamical Ising machines achieve accelerated solving of complex combinatorial optimization problems by remapping the convergence to the ground state of the classical spin networks to the evolution of specially constructed continuous…

Emerging Technologies · Computer Science 2025-12-30 Aditya Shukla , Mikhail Erementchouk , Pinaki Mazumder

Conceptual process design is a crucial aspect of chemical engineering that involves process synthesis. Mixed-integer nonlinear programming is a powerful framework for modeling such design problems by combining discrete and continuous…

Optimization and Control · Mathematics 2026-03-23 Yirang Park , David E. Bernal Neira

We propose a novel type of minor-embedding (ME) in simulated-annealing-based Ising machines. The Ising machines can solve combinatorial optimization problems. Many combinatorial optimization problems are mapped to find the ground…

Statistical Mechanics · Physics 2020-12-07 Tatsuhiko Shirai , Shu Tanaka , Nozomu Togawa

Population annealing is a Monte Carlo algorithm that marries features from simulated annealing and parallel tempering Monte Carlo. As such, it is ideal to overcome large energy barriers in the free-energy landscape while minimizing a…

Disordered Systems and Neural Networks · Physics 2015-07-08 Wenlong Wang , Jonathan Machta , Helmut G. Katzgraber

The Ising model provides a natural mapping for many computationally hard combinatorial optimization problems (COPs). Consequently, dynamical system-inspired computing models and hardware platforms that minimize the Ising Hamiltonian, have…

Dynamical Systems · Mathematics 2022-11-11 Mohammad Khairul Bashar , Nikhil Shukla

We carry out simulated annealing and employ a generalized Kibble-Zurek scaling hypothesis to study the 2D Ising spin glass with normal-distributed couplings. The system has an equilibrium glass transition at temperature $T=0$. From a…

Statistical Mechanics · Physics 2017-11-08 Na Xu , Kai-Hsin Wu , Shanon J. Rubin , Ying-Jer Kao , Anders W. Sandvik

We report the value of the dynamical critical exponent z for the six dimensional Ising spin glass, measured in three different ways: from the behavior of the energy and the susceptibility with the Monte Carlo time and by studying the…

Disordered Systems and Neural Networks · Physics 2009-10-30 Giorgio Parisi , Paola Ranieri , Federico Ricci-Tersenghi , Juan J. Ruiz-Lorenzo

A generalization of the Sherrington-Kirkpatrick (SK) model for spin glasses is considered, in which the interaction matrix is endowed with a variance profile that has no particular structure an may be sparse. In the first part of this…

Mathematical Physics · Physics 2026-04-29 Walid Hachem

Ising machines have attracted attention as efficient solvers for combinatorial optimization problems, which are formulated as ground-state (lowest-energy) search problems of the Ising model. Due to the limited bit-width of coefficients on…

Statistical Mechanics · Physics 2023-09-20 Shuta Kikuchi , Nozomu Togawa , Shu Tanaka

We investigate the minimization of Ising Hamiltonians, comparing the performance of gain-based computing paradigms based on the dynamics of semi-classical soft-spin models with quantum annealing. We systematically analyze how the energy…

Quantum Physics · Physics 2025-02-17 James S. Cummins , Hayder Salman , Natalia G. Berloff

Quantum annealing is a promising algorithm for solving combinatorial optimization problems. It searches for the ground state of the Ising model, which corresponds to the optimal solution of a given combinatorial optimization problem. The…

Statistical Mechanics · Physics 2026-02-25 Tomohiro Hattori , Shu Tanaka

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

This study focuses on the problem of finding ground states of random instances of the Sherrington-Kirkpatrick (SK) spin-glass model with Gaussian couplings. While the ground states of SK spin-glass instances can be obtained with branch and…

Disordered Systems and Neural Networks · Physics 2009-07-29 Martin Pelikan , Helmut G. Katzgraber , Sigismund Kobe

Extremal Optimization (EO), a new local search heuristic, is used to approximate ground states of the mean-field spin glass model introduced by Sherrington and Kirkpatrick. The implementation extends the applicability of EO to systems with…

Disordered Systems and Neural Networks · Physics 2022-05-20 Stefan Boettcher

We study the non-equilibrium dynamics of kicked Ising models in $1+1$ dimensions which have interactions alternating between odd and even bonds in time. These models can be understood as quantum circuits tiling space-time with the…

Quantum Physics · Physics 2025-03-18 Chuan Liu , Wen Wei Ho

Spin glasses are disordered magnets with random interactions that are, generally, in conflict with each other. Finding the ground states of spin glasses is not only essential for the understanding of the nature of disordered magnetic and…

Disordered Systems and Neural Networks · Physics 2021-09-30 Changjun Fan , Mutian Shen , Zohar Nussinov , Zhong Liu , Yizhou Sun , Yang-Yu Liu

Continuum manipulators have gained significant attention as a promising alternative to rigid manipulators, offering notable advantages in terms of flexibility and adaptability within intricate workspace. However, the broader application of…

Robotics · Computer Science 2024-10-29 Yinan Sun , Sai Wang

All ground states and low-lying excitations of a +/- I Ising spin glass model on a cubic 4 x 4 x 4 lattice with periodical boundary conditions were calculated using a method of combinatorical optimization. The structure of states in the…

Condensed Matter · Physics 2016-08-31 T. Klotz , S. Kobe

The dynamics of an asymmetric kinetic Ising model is studied. Two schemes for improving the existing mean-field description are proposed. In the first scheme, we derive the formulas for instantaneous magnetization, equal-time correlation,…

Disordered Systems and Neural Networks · Physics 2014-05-23 Haiping Huang , Yoshiyuki Kabashima

Discrete combinatorial optimization consists in finding the optimal configuration that minimizes a given discrete objective function. An interpretation of such a function as the energy of a classical system allows us to reduce the…

Quantum Physics · Physics 2015-06-22 Sergio Boixo , Gerardo Ortiz , Rolando Somma
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