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Ising Machines (IMs) are physical systems designed to find solutions to combinatorial optimization (CO) problems mapped onto the IM via the coupling strengths of its binary spins. Using the intrinsic dynamics and different annealing…

Mesoscale and Nanoscale Physics · Physics 2020-06-04 Afshin Houshang , Mohammad Zahedinejad , Shreyas Muralidhar , Jakub Checinski , Ahmad A. Awad , Johan Åkerman

It has recently been shown that optical parametric oscillator (OPO) Ising machines, consisting of coupled optical pulses circulating in a cavity with parametric gain, can be used to probabilistically find low-energy states of Ising spin…

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

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

Analog computing using bosonic computational states is a leading approach to surpassing the computational speed and energy limitations of von Neumann architectures. But the challenges of manufacturing large-scale photonic integrated…

Optics · Physics 2025-07-22 Farhad Khosravi , Martin Perreault , Artur Scherer , Pooya Ronagh

The past decade has seen the emergence of Ising machines targeting hard combinatorial optimization problems by minimizing the Ising Hamiltonian with spins represented by continuous dynamical variables. However, capabilities of these…

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

Dynamical Ising machines are actively investigated from the perspective of finding efficient heuristics for NP-hard optimization problems. However, the existing data demonstrate super-polynomial scaling of the running time with the system…

Statistical Mechanics · Physics 2022-05-24 Mikhail Erementchouk , Aditya Shukla , Pinaki Mazumder

Conventional computing architectures have no known efficient algorithms for combinatorial optimization tasks, which are encountered in fundamental areas and real-world practical problems including logistics, social networks, and…

Ising machines offer a compelling approach to addressing NP-hard problems, but physical realizations that are simultaneously scalable, reconfigurable, fast, and stable remain elusive. Quantum annealers, like D-Wave's cryogenic hardware,…

A promising approach to achieve computational supremacy over the classical von Neumann architecture explores classical and quantum hardware as Ising machines. The minimisation of the Ising Hamiltonian is known to be NP-hard problem for…

Quantum Physics · Physics 2020-08-04 Kirill P. Kalinin , Natalia G. Berloff

The development of physical simulators, called Ising machines, that sample from low energy states of the Ising Hamiltonian has the potential to drastically transform our ability to understand and control complex systems. However, most of…

Computational Physics · Physics 2021-03-10 Timothee Leleu , Farad Khoyratee , Timothee Levi , Ryan Hamerly , Takashi Kohno , Kazuyuki Aihara

Ising machines are physical platforms designed to minimize the energy of classical Ising Hamiltonians, yet accessing specific excited states remains an open challenge of both fundamental and practical relevance. In this letter we show that…

Quantum Physics · Physics 2026-04-15 Jacopo Tosca , Cristiano Ciuti , Claudio Conti , Marcello Calvanese Strinati

The coherent Ising machine is expected to find a near-optimal solution in various combinatorial optimization problems, which has been experimentally confirmed with optical parametric oscillators (OPOs) and a field programmable gate array…

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

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

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…

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 nonconventional hardware architecture for finding approximate solutions to large-scale combinatorial optimization problems. It operates by annealing a laser gain parameter to adiabatically deform a…

Disordered Systems and Neural Networks · Physics 2025-10-28 Federico Ghimenti , Adithya Sriram , Atsushi Yamamura , Hideo Mabuchi , Surya Ganguli

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

Efficiently optimizing Nondeterministic Polynomial time (NP) problems in polynomial time has profound implications in many domains. CMOS oscillator networks have been shown to be effective and efficient in approximating certain NP-hard…

Emerging Technologies · Computer Science 2025-09-18 Wenxiao Cai , Zongru Li , Yu-Neng Wang , Sara Achour , Thomas H. Lee