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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

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

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…

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…

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

Ising machines (IMs) are specialized devices designed to efficiently solve combinatorial optimization problems (COPs). They consist of artificial spins that evolve towards a low-energy configuration representing a problem's solution. Most…

Oscillator Ising machines (OIMs) represent an exemplar case of using physics-inspired non-linear dynamical systems to solve computationally challenging combinatorial optimization problems (COPs). The computational performance of such…

Machine Learning · Computer Science 2025-04-15 E. M. H. E. B. Ekanayake , N. Shukla

Combinatorial optimization problems are ubiquitous in industrial applications. However, finding optimal or close-to-optimal solutions can often be extremely hard. Because some of these problems can be mapped to the ground-state search of…

Quantum Physics · Physics 2025-09-04 Junpeng Hou , Amin Barzegar , Helmut G. Katzgraber

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

Coherent Ising Machine (CIM) is a network of optical parametric oscillators that solves combinatorial optimization problems by finding the ground state of an Ising Hamiltonian. In CIMs, a problem arises when attempting to realize the Zeeman…

The reliable simulation of spin models is of critical importance to tackle complex optimization problems that are intractable on conventional computing machines. The recently introduced hyperspin machine, which is a network of linearly and…

Computational Physics · Physics 2025-11-05 Marcello Calvanese Strinati , Claudio Conti

Quantum phase transitions (QPTs) in coherent Ising machines (CIMs) are studied via a spectral mapping between the one-dimensional XY spin model and a network of degenerate optical parametric oscillators (DOPOs). This exact correspondence…

Quantum Physics · Physics 2025-12-30 Jing-Yi-Ran Jin , Shuang-Quan Ma , Qing Ai

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

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

Solving combinatorial optimization problems efficiently through emerging hardware by converting the problem to its equivalent Ising model and obtaining its ground state is known as Ising computing. Phase-binarized oscillators (PBO), modeled…

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

Optical parametric oscillators (OPOs) have been widely used for decades as tunable, narrow linewidth, and coherent light sources for reaching long wavelengths and are attractive for applications such as quantum random number generation and…

The ground state search of the Ising model can be used to solve many combinatorial optimization problems. Under the current computer architecture, an Ising ground state search algorithm suitable for hardware computing is necessary for…

Computational Physics · Physics 2023-05-15 Zhelong Jiang , Gang Chen , Ruixiu Qiao , Pengcheng Feng , Yihao Chen , Junjia Su , Zhiyuan Zhao , Min Jin , Xu Chen , Zhigang Li , Huaxiang Lu

The spatial photonic Ising machine (SPIM) [D. Pierangeli et al., Phys. Rev. Lett. 122, 213902 (2019)] is a promising optical architecture utilizing spatial light modulation for solving large-scale combinatorial optimization problems…

Disordered Systems and Neural Networks · Physics 2023-08-09 Hiroshi Yamashita , Ken-ichi Okubo , Suguru Shimomura , Yusuke Ogura , Jun Tanida , Hideyuki Suzuki

Recent work has shown that probabilistic models based on pairwise interactions-in the simplest case, the Ising model-provide surprisingly accurate descriptions of experiments on real biological networks ranging from neurons to genes.…

Quantitative Methods · Quantitative Biology 2007-12-18 Tamara Broderick , Miroslav Dudik , Gasper Tkacik , Robert E. Schapire , William Bialek