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Quantum and classical physics can be used for mathematical computations that are hard to tackle by conventional electronics. Very recently, optical Ising machines have been demonstrated for computing the minima of spin Hamiltonians, paving…

Optics · Physics 2019-06-26 D. Pierangeli , G. Marcucci , C. Conti

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…

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…

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

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…

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

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

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

This paper proposes a space-division multiplexed spatial-photonic Ising machine (SDM-SPIM) that physically calculates the weighted sum of the Ising Hamiltonians for individual components in a multi-component model. Space-division…

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

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…

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

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

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 one-dimensional Ising model with its connections to several physical concepts plays a vital role in comprehension of several principles, phenomena and numerical methods. The Hamiltonian of a coupled one-dimensional dissipative spin…

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

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

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

On-chip analog Ising Machines (IMs) are a promising means to solve difficult combinatorial optimization problems. For scalable on-chip realizations to be practical, 1) the problem should map scalably to Ising form, 2) interconnectivity…

Emerging Technologies · Computer Science 2023-10-03 Thomas Jagielski , Rajit Manohar , Jaijeet Roychowdhury

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
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