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Demonstration of chip-based coupled degenerate optical parametric oscillators for realizing a nanophotonic spin-glass

Author

Listed:
  • Yoshitomo Okawachi

    (Columbia University)

  • Mengjie Yu

    (Columbia University
    Cornell University)

  • Jae K. Jang

    (Columbia University)

  • Xingchen Ji

    (Columbia University)

  • Yun Zhao

    (Columbia University)

  • Bok Young Kim

    (Columbia University)

  • Michal Lipson

    (Columbia University
    Columbia University)

  • Alexander L. Gaeta

    (Columbia University
    Columbia University)

Abstract

The need for solving optimization problems is prevalent in various physical applications, including neuroscience, network design, biological systems, socio-economics, and chemical reactions. Many of these are classified as non-deterministic polynomial-time hard and thus become intractable to solve as the system scales to a large number of elements. Recent research advances in photonics have sparked interest in using a network of coupled degenerate optical parametric oscillators (DOPOs) to effectively find the ground state of the Ising Hamiltonian, which can be used to solve other combinatorial optimization problems through polynomial-time mapping. Here, using the nanophotonic silicon-nitride platform, we demonstrate a spatial-multiplexed DOPO system using continuous-wave pumping. We experimentally demonstrate the generation and coupling of two microresonator-based DOPOs on a single chip. Through a reconfigurable phase link, we achieve both in-phase and out-of-phase operation, which can be deterministically achieved at a fast regeneration speed of 400 kHz with a large phase tolerance.

Suggested Citation

  • Yoshitomo Okawachi & Mengjie Yu & Jae K. Jang & Xingchen Ji & Yun Zhao & Bok Young Kim & Michal Lipson & Alexander L. Gaeta, 2020. "Demonstration of chip-based coupled degenerate optical parametric oscillators for realizing a nanophotonic spin-glass," Nature Communications, Nature, vol. 11(1), pages 1-7, December.
  • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-17919-6
    DOI: 10.1038/s41467-020-17919-6
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    Cited by:

    1. Juntao Wang & Daniel Ebler & K. Y. Michael Wong & David Shui Wing Hui & Jie Sun, 2023. "Bifurcation behaviors shape how continuous physical dynamics solves discrete Ising optimization," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    2. Marcello Calvanese Strinati & Claudio Conti, 2022. "Multidimensional hyperspin machine," Nature Communications, Nature, vol. 13(1), pages 1-10, December.

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