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Recently, the coherent Ising machine (CIM) as a degenerate optical parametric oscillator (DOPO) network has been researched to solve Ising combinatorial optimization problems. We formulate a theoretical model for the CIM with discrete-time…

Quantum Physics · Physics 2017-11-22 Atsushi Yamamura , Kazuyuki Aihara , Yoshihisa Yamamoto

The coherent Ising machine (CIM) enables efficient sampling of low-lying energy states of the Ising Hamiltonian with all-to-all connectivity by encoding the spins in the amplitudes of pulsed modes in an optical parametric oscillator (OPO).…

Quantum Physics · Physics 2021-03-22 Egor S. Tiunov , Alexander E. Ulanov , A. I. Lvovsky

Decades of exponential scaling in high performance computing (HPC) efficiency is coming to an end. Transistor based logic in complementary metal-oxide semiconductor (CMOS) technology is approaching physical limits beyond which further…

Machine Learning · Computer Science 2024-02-01 Fiona Knoll , John T. Daly , Jess J. Meyer

Ising machines are hardware solvers which aim to find the absolute or approximate ground states of the Ising model. The Ising model is of fundamental computational interest because it is possible to formulate any problem in the complexity…

Quantum Physics · Physics 2022-04-04 Naeimeh Mohseni , Peter L. McMahon , Tim Byrnes

The growing challenges of scaling digital computing motivate new approaches, especially through the dynamical evolution of physical systems that mimic neural networks and combinatorial optimization problems. While light is a hyper efficient…

Many tasks in our modern life, such as planning an efficient travel, image processing and optimizing integrated circuit design, are modeled as complex combinatorial optimization problems with binary variables. Such problems can be mapped to…

We propose a network of open-dissipative quantum oscillators with optical error correction circuits. In the proposed network, the squeezed/anti-squeezed vacuum states of the constituent optical parametric oscillators below the threshold…

Quantum Physics · Physics 2021-08-18 Sam Reifenstein , Satoshi Kako , Farad Khoyratee , Timothée Leleu , Yoshihisa Yamamoto

Coupled parametric oscillators were recently employed as simulators of artificial Ising networks, with the potential to solve computationally hard minimization problems. We demonstrate a new dynamical regime within the simplest network -…

We present a new way to make Ising machines, i.e., using networks of coupled self-sustaining nonlinear oscillators. Our scheme is theoretically rooted in a novel result that establishes that the phase dynamics of coupled oscillator systems,…

Emerging Technologies · Computer Science 2019-03-19 Tianshi Wang , Jaijeet Roychowdhury

Periodically driven parametric oscillators offer a convenient way to simulate classical Ising spins. When many parametric oscillators are coupled dissipatively, they can be analogous to networks of Ising spins, forming an effective coherent…

Ising Machines are emerging hardware architectures that efficiently solve NP-Hard combinatorial optimization problems. Generally, combinatorial problems are transformed into quadratic unconstrained binary optimization (QUBO) form, but this…

Hardware Architecture · Computer Science 2025-09-12 Chirag Garg , Sayeef Salahuddin

Quantum machine learning with variational quantum algorithms (VQA) has been actively investigated as a practical algorithm in the noisy intermediate-scale quantum (NISQ) era. Recent researches reveal that the data reuploading, which…

Quantum Physics · Physics 2024-03-06 Yuichiro Mori , Kouhei Nakaji , Yuichiro Matsuzaki , Shiro Kawabata

Coherent Ising Machine (CIM) is a network of optical parametric oscillators that can solve large-scale combinatorial optimisation problems by finding the ground state of an Ising Hamiltonian. As a practical application of CIM, Aonishi et…

Coherent Ising Machines (CIMs) have emerged as a hybrid form of quantum computing devices designed to solve NP-complete problems, offering an exciting opportunity for discovering optimal solutions. Despite challenges such as susceptibility…

Kerr parametric oscillators (KPOs) have attracted increasing attention in terms of their application to quantum information processing and quantum simulations. The state preparation and measurement of KPOs are typical requirements when they…

Quantum Physics · Physics 2022-08-10 Yuta Suzuki , Shohei Watabe , Shiro Kawabata , Shumpei Masuda

The $q$-state Potts model is a fundamental model in statistical physics that generalizes the Ising model and plays a key role in the study of phase transitions, critical phenomena, complex systems, and combinatorial optimization. Sampling…

Statistical Mechanics · Physics 2026-01-07 Yi Cheng , Zongli Lin

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

We contribute to the mathematical theory of the design of low temperature Ising machines, a type of experimental probabilistic computing device implementing the Ising model. Encoding the output of a function in the ground state of a…

Emerging Technologies · Computer Science 2025-07-18 Andrew G. Moore , Zachary Richey , Isaac K. Martin

We study large networks of parametric oscillators as heuristic solvers of random Ising models. In these networks, known as coherent Ising machines, the model to be solved is encoded in the coupling between the oscillators, and a solution is…

Statistical Mechanics · Physics 2021-04-12 Marcello Calvanese Strinati , Leon Bello , Emanuele G. Dalla Torre , Avi Pe'er

Networks of coupled nonlinear oscillators are emerging as powerful physical platforms for implementing Ising machines. Yet the relationship between parametric-oscillator implementations and traditional oscillator-based Ising machines…

Systems and Control · Electrical Eng. & Systems 2025-10-29 Nikhat Khan , E. M. H. E. B. Ekanayake , Nicolas Casilli , Cristian Cassella , Luke Theogarajan , Nikhil Shukla