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As a quantum-inspired, non-traditional analog solver architecture, the analog Ising machine (AIM) has emerged as a distinctive computational paradigm to address the rapidly growing demand for computational power. However, the mathematical…

Quantum Physics · Physics 2026-02-06 Langyu Li , Ruoyu Wu , Yong Wang , Guofeng Zhang , Jinhu Lü , Qing Gao , Yu Pan

Many real-time systems require the optimization of discrete variables. Black-box optimization (BBO) algorithms and multi-armed bandit (MAB) algorithms perform optimization by repeatedly taking actions and observing the corresponding instant…

Artificial Intelligence · Computer Science 2025-06-23 Tomoya Kashimata , Yohei Hamakawa , Masaya Yamasaki , Kosuke Tatsumura

Airfoil shape optimization presents a challenge where classical solvers frequently struggle with computational efficiency and local minima. In the promising paradigm of quantum computing, the coherent Ising machine (CIM), a specialized…

Quantum Physics · Physics 2026-03-12 Hao Ni , Qi Gao , Zhen Lu , Yue Yang

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

A prominent approach to solving combinatorial optimization problems on parallel hardware is Ising machines, i.e., hardware implementations of networks of interacting binary spin variables. Most Ising machines leverage second-order…

Emerging Technologies · Computer Science 2022-12-08 Connor Bybee , Denis Kleyko , Dmitri E. Nikonov , Amir Khosrowshahi , Bruno A. Olshausen , Friedrich T. Sommer

Many combinatorial optimization problems can be reformulated as finding the ground state of the Ising model. Existing Ising solvers are mostly inspired by simulated annealing. Although annealing techniques offer scalability, they lack…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-12-11 Debraj Banerjee , Santanu Mahapatra , Kunal Narayan Chaudhury

The coherent Ising machine (CIM) is a quantum-inspired computing platform that leverages optical parametric oscillation dynamics to solve combinatorial optimization problems by searching for the ground state of an Ising Hamiltonian.…

Quantum Physics · Physics 2025-09-18 Yan Chen Jiang , Lu Ma , Chuan Wang , Tie Jun Wang

Ising machines, which are dynamical systems designed to operate in a parallel and iterative manner, have emerged as a new paradigm for solving combinatorial optimization problems. Despite computational advantages, the quality of solutions…

Statistical Mechanics · Physics 2026-01-30 Shu Zhou , K. Y. Michael Wong , Juntao Wang , David Shui Wing Hui , Daniel Ebler , Jie Sun

A spinwave Ising machine (SWIM) is a newly proposed type of time-multiplexed hardware solver for combinatorial optimization that employs feedback coupling and phase sensitive amplification to map an Ising Hamiltonian into phase-binarized…

Mesoscale and Nanoscale Physics · Physics 2023-08-16 Victor H. González , Artem Litvinenko , Roman Khymyn , Johan Åkerman

Quantum or quantum-inspired Ising machines have recently shown promise in solving combinatorial optimization problems in a short time. Real-world applications, such as time division multiple access (TDMA) scheduling for wireless multi-hop…

Emerging Technologies · Computer Science 2025-04-03 Yohei Hamakawa , Tomoya Kashimata , Masaya Yamasaki , Kosuke Tatsumura

Oscillator Ising Machines (OIMs) and probabilistic bit (p-bit)-based computing platforms have emerged as promising paradigms for tackling complex combinatorial optimization problems. Although traditionally viewed as distinct approaches,…

Computational Physics · Physics 2026-01-26 E. M. Hasantha Ekanayake , Nikhat Khan , Nikhil Shukla

We propose a data-driven heuristic for NP-hard Ising and Max-Cut optimization that learns the update rule of an iterative dynamical system. The method learns a shared, node-wise update rule that maps local interaction fields to spin…

Machine Learning · Computer Science 2026-02-03 Sam Reifenstein , Timothee Leleu

In this paper, we report new results on a novel Ising machine technology for solving combinatorial optimization problems using networks of coupled self-sustaining oscillators. Specifically, we present several working hardware prototypes…

Emerging Technologies · Computer Science 2019-04-24 Tianshi Wang , Leon Wu , Jaijeet Roychowdhury

We present an oscillator model with both phase and amplitude dynamics for oscillator-based Ising machines (OIMs). The model targets combinatorial optimization problems with polynomial cost functions of arbitrary order and addresses…

Emerging Technologies · Computer Science 2026-03-17 Lianlong Sun , Matthew X. Burns , Michael C. Huang

This paper proposes a novel optimization framework for discrete phase shifts of a reconfigurable intelligent surface (RIS) using a coherent Ising machine (CIM). Unlike conventional methods based on iterative convex approximation or…

Information Theory · Computer Science 2026-04-01 Yuto Hama , Daisuke Kitayama , Kensuke Inaba , Toshimori Honjo , Hiroki Takesue , Naoki Ishikawa , Hiroyuki Takahashi

The Ising machine is an unconventional computing architecture that can be used to solve NP-hard combinatorial optimization problems more efficiently than traditional von Neumann architectures. Fast, compact oscillator networks which provide…

Computational Physics · Physics 2021-10-20 Brooke C. McGoldrick , Jonathan Z. Sun , Luqiao Liu

Combinatorial optimization problems are computationally hard in general, but they are ubiquitous in our modern life. A coherent Ising machine (CIM) based on a multiple-pulse degenerate optical parametric oscillator (DOPO) is an alternative…

The Coherent Ising Machine (CIM) is a non-conventional architecture that takes inspiration from physical annealing processes to solve Ising problems heuristically. Its dynamics are naturally continuous and described by a set of ordinary…

Optimization and Control · Mathematics 2024-01-23 Robin Brown , Davide Venturelli , Marco Pavone , David E. Bernal Neira

Given the fundamental importance of combinatorial optimization across many diverse application domains, there has been widespread interest in the development of unconventional physical computing architectures that can deliver better…

Disordered Systems and Neural Networks · Physics 2023-09-18 Atsushi Yamamura , Hideo Mabuchi , Surya Ganguli

We show that the nonlinear stochastic dynamics of a measurement-feedback-based coherent Ising machine (MFB-CIM) in the presence of quantum noise can be exploited to sample degenerate ground and low-energy spin configurations of the Ising…

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