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A systematic study of both classical and quantum geometric frustrated Ising models with a competing ordering mechanism is reported in this paper. The ordering comes in the classical case from a coupling of 2D layers and in the quantum model…

Statistical Mechanics · Physics 2007-05-23 Ying Jiang , Thorsten Emig

Four decades after Richard Feynman's famous remark, we have reached a stage at which nature can be simulated quantum mechanically. Quantum simulation is among the most promising applications of quantum computing. However, like many quantum…

Quantum Physics · Physics 2026-02-17 Mahmood Hasani , Hadis Salasi , Negar Ashari Astani

We explore the potential of spatial-photonic Ising machines (SPIMs) to address computationally intensive Ising problems that employ low-rank and circulant coupling matrices. Our results indicate that the performance of SPIMs is critically…

This paper introduces the Kaiwu-PyTorch-Plugin (KPP) to bridge Deep Learning and Photonic Quantum Computing across multiple dimensions. KPP integrates the Coherent Ising Machine into the PyTorch ecosystem, addressing classical…

Quantum Physics · Physics 2026-02-24 Hongdong Zhu , Qi Gao , Yin Ma , Shaobo Chen , Haixu Liu , Fengao Wang , Tinglan Wang , Chang Wu , Kai Wen

We present a sampling-based Model Predictive Control (MPC) method that implements Model Predictive Path Integral (MPPI) as an \emph{Ising machine}, suitable for novel forms of probabilistic computing. By expressing the control problem as a…

Systems and Control · Electrical Eng. & Systems 2025-12-18 Lorin Werthen-Brabants , Pieter Simoens

Neural quantum states efficiently represent many-body wavefunctions with neural networks, but the cost of Monte Carlo sampling limits their scaling to large system sizes. Here we address this challenge by combining sparse Boltzmann machine…

Dynamical Ising machines are continuous dynamical systems that evolve from a generic initial state to a state strongly related to the ground state of the classical Ising model. We show that such a machine driven by the V${}_2$ dynamical…

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

Self-induced stochastic resonance (SISR) is the emergence of coherent oscillations in slow-fast excitable systems driven solely by noise, without external periodic forcing or proximity to a bifurcation. This work presents a physics-informed…

Machine Learning · Computer Science 2026-01-29 Divyesh Savaliya , Marius E. Yamakou

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…

While there are various approaches to benchmark physical processors, recent findings have focused on computational phase transitions. This is due to several factors. Importantly, the hardest instances appear to be well-concentrated in a…

Quantum Physics · Physics 2021-04-08 Hariphan Philathong , Vishwa Akshay , Ksenia Samburskaya , Jacob Biamonte

Systems of coupled optical parametric oscillators (OPOs) forming an Ising machine are emerging as large-scale simulators of the Ising model. The advances in computer science and nonlinear optics have triggered not only the physical…

Quantum Physics · Physics 2024-06-25 Marcello Calvanese Strinati , Claudio Conti

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…

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

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

Probabilistic Ising machines (PIMs) provide a path to solving many computationally hard problems more efficiently than deterministic algorithms on von Neumann computers. Stochastic magnetic tunnel junctions (S-MTJs), which are engineered to…

A method of quantum annealing (QA) using Kerr-nonlinear parametric oscillators (KPOs) was proposed. This method is described by bosonic operators and has different characteristics from QA based on the transverse-field Ising model. As the…

Quantum Physics · Physics 2022-07-05 Ryoji Miyazaki

Reducing the impact of seismic activity on the motion of suspended optics is essential for the operation of ground-based gravitational wave detectors. During periods of increased seismic activity, low-frequency ground translation and tilt…

Instrumentation and Methods for Astrophysics · Physics 2020-08-31 Jonathan J. Carter , Sam J. Cooper , Edward Thrift , Joseph Briggs , Jim Warner , Michael P. Ross , Conor M. Mow-Lowry

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. As a practical application of CIM, Aonishi et al. proposed a…

A quantum simulator is a well controlled quantum system that can simulate the behavior of another quantum system which may require exponentially large classical computing resources to understand otherwise. In the 1980s, Feynman proposed the…

We investigate the classical dynamics of optical nonlinear Kerr couplers, focusing on their potential relevance to quantum computing applications. The system consists of three Kerr-type nonlinear oscillators arranged in two configurations:…

Chaotic Dynamics · Physics 2025-08-25 K. Chmielewski , K. Grygiel , K. Bartkiewicz