
1.State Key Laboratory on Integrated Optoelectronics, Institute of Semiconductors, Chinese Academy of Sciences, Beijing, China
2.School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, China
3.Center of Materials Science and Optoelectronics Engineering, University of Chinese Academy of Sciences, Beijing, China
4.State Key Laboratory of Information Photonics and Optical Communications, Beijing University of Posts and Telecommunications, Beijing, China
5.School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai, China
6.Peng Cheng Laboratory, Shenzhen, China
Yitang Dai (ytdai@bupt.edu.cn)
Ming Li (ml@semi.ac.cn)
Published:31 December 2022,
Published Online:25 November 2022,
Received:07 May 2022,
Revised:08 October 2022,
Accepted:11 October 2022
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Cen, Q. Z. et al. Large-scale coherent Ising machine based on optoelectronic parametric oscillator. Light: Science & Applications, 11, 2972-2981 (2022).
Cen, Q. Z. et al. Large-scale coherent Ising machine based on optoelectronic parametric oscillator. Light: Science & Applications, 11, 2972-2981 (2022). DOI: 10.1038/s41377-022-01013-1.
Ising machines based on analog systems have the potential to accelerate the solution of ubiquitous combinatorial optimization problems. Although some artificial spins to support large-scale Ising machines have been reported
e.g.
superconducting qubits in quantum annealers and short optical pulses in coherent Ising machines
the spin stability is fragile due to the ultra-low equivalent temperature or optical phase sensitivity. In this paper
we propose to use short microwave pulses generated from an optoelectronic parametric oscillator as the spins to implement a large-scale Ising machine with high stability. The proposed machine supports 25
600 spins and can operate continuously and stably for hours. Moreover
the proposed Ising machine is highly compatible with high-speed electronic devices for programmability
paving a low-cost
accurate
and easy-to-implement way toward solving real-world optimization problems.
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