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Recently, spatial photonic Ising machines (SPIM) have been demonstrated to compute the minima of Hamiltonians for large-scale spin systems. Here we propose to implement an antiferromagnetic model through optoelectronic correlation computing…

Emerging Technologies · Computer Science 2021-11-15 Junyi Huang , Yisheng Fang , Zhichao Ruan

Spin glasses featured by frustrated interactions and metastable states have important applications in chemistry, material sciences and artificial neural networks. However, the solution of the spin glass models is hindered by the…

Disordered Systems and Neural Networks · Physics 2023-10-24 Weiru Fan , Yuxuan Sun , Xingqi Xu , Da-Wei Wang , Shi-Yao Zhu , Hai-Qing Lin

Ising machines are an emerging class of hardware that promises ultrafast and energy-efficient solutions to NP-hard combinatorial optimization problems. Spatial photonic Ising machines (SPIMs) exploit optical computing in free space to…

Ising machines are emerging as a powerful physical alternative to digital processors for solving combinatorial optimization problems. Among them, spatial photonic Ising machines (SPIMs) offer compact, room-temperature hardware with…

Networks of optical oscillators simulating coupled Ising spins have been recently proposed as a heuristic platform to solve hard optimization problems. These networks, called coherent Ising machines (CIMs), exploit the fact that the…

Emerging Technologies · Computer Science 2021-11-15 Marcello Calvanese Strinati , Davide Pierangeli , Claudio Conti

Optical simulators for the Ising model have demonstrated great promise for solving challenging problems in physics and beyond. Here, we develop a spatial optical simulator for a variety of classical statistical systems, including the clock,…

Optics · Physics 2024-12-19 Song-Tao Yu , Ming-Gen He , Sheng Fang , Youjin Deng , Zhen-Sheng Yuan

Recently, spatial photonic Ising machines (SPIMs) have demonstrated the abilities to compute the Ising Hamiltonian of large-scale spin systems, with the advantages of ultrafast speed and high power efficiency. However, such optical…

Optics · Physics 2024-01-17 Li Luo , Zhiyi Mi , Junyi Huang , Zhichao Ruan

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

The race to heuristically solve non-deterministic polynomial-time (NP) problems through efficient methods is ongoing. Recently, optics was demonstrated as a promising tool to find the ground state of a spin-glass Ising Hamiltonian, which…

Disordered Systems and Neural Networks · Physics 2022-03-14 Gianni Jacucci , Louis Delloye , Davide Pierangeli , Mushegh Rafayelyan , Claudio Conti , Sylvain Gigan

Photonic Ising Machines constitute an emergent new paradigm of computation, geared towards tackling combinatorial optimization problems that can be reduced to the problem of finding the ground state of an Ising model. Spatial Photonic Ising…

Spatial photonic Ising machines offer a novel optical platform for optimization and spin-model simulation, but existing diffraction-based schemes rely on auxiliary spins or multiplexing to encode high-rank couplings and external fields,…

Optics · Physics 2026-05-12 Ze Zheng , Yuegang Li , Hang Xu , Jingzheng Huang , Tailong Xiao , Guihua Zeng

Ising machines based on analog systems have the potential of acceleration in solving ubiquitous combinatorial optimization problems. Although some artificial spins to support large-scale Ising machine is reported, e.g. superconducting…

Applied Physics · Physics 2020-11-03 Qizhuang Cen , Tengfei Hao , Hao Ding , Shanhong Guan , Zhiqiang Qin , Kun Xu , Yitang Dai , Ming Li

A spatial photonic Ising machine (SPIM) handles large-scale combinatorial optimization problems owing to optical processing with spatial parallelism. However, iterative feedback in the search for optimal solutions limits processing speed…

Optics · Physics 2025-02-27 Suguru Shimomura , Jun Tanida , Yusuke Ogura

The general-purpose programmable photonic processors offer a scalable and reconfigurable solution for a wide range of RF and optical applications. Therefore, implementing photonic Ising machines using programmable processors leverages the…

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

Finding the ground states of the Ising Hamiltonian [1] maps to various combinatorial optimization problems in biology, medicine, wireless communications, artificial intelligence, and social network. So far no efficient classical and quantum…

Quantum Physics · Physics 2014-10-30 Alireza Marandi , Zhe Wang , Kenta Takata , Robert L. Byer , Yoshihisa Yamamoto

To tackle challenging combinatorial optimization problems, analog computing machines based on the nature-inspired Ising model are attracting increasing attentions in order to disruptively overcome the impending limitations on conventional…

Emerging Technologies · Computer Science 2023-12-07 Xin Ye , Wenjia Zhang , Shaomeng Wang , Xiaoxuan Yang , Zuyuan He

Statistical spin dynamics plays a key role to understand the working principle for novel optical Ising machines. Here we propose the gauge transformations for spatial photonic Ising machine, where a single spatial phase modulator…

Disordered Systems and Neural Networks · Physics 2021-07-28 Yisheng Fang , Junyi Huang , Zhichao Ruan

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

Many developments in science and engineering depend on tackling complex optimizations on large scales. The challenge motivates intense search for specific computing hardware that takes advantage from quantum features, nonlinear dynamics, or…

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