A coherent Ising machine for 2000-node optimization problems-Reference-Cited by-同舟云学术

A coherent Ising machine for 2000-node optimization problems

Published:2016-11-04 Issue:6312 Volume:354 Page:603-606
ISSN:0036-8075
Container-title:Science
language:en
Short-container-title:Science

Author:

Inagaki Takahiro¹,Haribara Yoshitaka²³⁴,Igarashi Koji⁵,Sonobe Tomohiro⁴⁶,Tamate Shuhei⁴,Honjo Toshimori¹,Marandi Alireza⁷,McMahon Peter L.⁷,Umeki Takeshi⁸,Enbutsu Koji⁸,Tadanaga Osamu⁸,Takenouchi Hirokazu⁸,Aihara Kazuyuki²³,Kawarabayashi Ken-ichi⁴⁶,Inoue Kyo⁵,Utsunomiya Shoko⁴,Takesue Hiroki¹

Affiliation:

1. NTT Basic Research Laboratories, NTT Corporation, 3-1 Morinosato Wakamiya, Atsugi, Kanagawa 243-0198, Japan.

2. Department of Mathematical Informatics, University of Tokyo, Hongo 7-3-1, Bunkyo-ku, Tokyo 113-8656, Japan.

3. Institute of Industrial Science, University of Tokyo, 4-6-1, Komaba, Meguro-ku, Tokyo 153-8505, Japan.

4. National Institute of Informatics, Hitotsubashi 2-1-2, Chiyoda-ku, Tokyo 101-8403, Japan.

5. Division of Electrical, Electronic and Information Engineering, Osaka University, Osaka 565-0871, Japan.

6. ERATO Kawarabayashi Large Graph Project, Japan Science and Technology Agency, Hitotsubashi 2-1-2, Chiyoda-ku, Tokyo 101-8403, Japan.

7. E. L. Ginzton Laboratory, Stanford University, Stanford, CA 94305, USA.

8. NTT Device Technology Laboratories, NTT Corporation, 3-1 Morinosato Wakamiya, Atsugi, Kanagawa 243-0198, Japan.

Abstract

Taking the pulse of optimization Finding the optimum solution of multiparameter or multifunctional problems is important across many disciplines, but it can be computationally intensive. Many such problems defined as computationally difficult can be mathematically mapped onto the so-called Ising problem, which looks at finding the minimum energy configuration for an array of coupled spins. Inagaki et al. and McMahon et al. show that an optical processing approach based on a network of coupled optical pulses in a ring fiber can be used to model and optimize large-scale Ising systems. Such a scalable architecture could help to optimize solutions to a wide range of complex problems. Science , this issue pp. 603 and 614

Funder

ImPACT

Publisher

American Association for the Advancement of Science (AAAS)

Subject

Multidisciplinary

Reference30 articles.

1. R. M. Karp Complexity of Computer Computations (Plenum 1972) pp. 85–103.

2. Optimization by Simulated Annealing

3. On the computational complexity of Ising spin glass models

4. Quantum annealing with manufactured spins

5. Quantum simulation of frustrated Ising spins with trapped ions

Cited by 500 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Compute-in-Memory Annealing Processor With Interaction Coefficient Reuse and Sparse Energy Computation for Solving Combinatorial Optimization Problems;IEEE Journal of Solid-State Circuits;2024-09

2. Frequency tunable CMOS ring oscillator‐based Ising machine;International Journal of Circuit Theory and Applications;2024-08-31

3. Enhanced DBR mirror design via D3QN: A reinforcement learning approach;PLOS ONE;2024-08-22

4. A scalable universal Ising machine based on interaction-centric storage and compute-in-memory;Nature Electronics;2024-08-13

5. Spintronic devices as next-generation computation accelerators;Current Opinion in Solid State and Materials Science;2024-08