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A single shot coherent Ising machine based on a network of injection-locked multicore fiber lasers

Author

Listed:
  • Masoud Babaeian

    (University of Arizona
    University of Arizona)

  • Dan T. Nguyen

    (University of Arizona
    Corning Research and Development Corporation)

  • Veysi Demir

    (ASML Corp)

  • Mehmetcan Akbulut

    (University of Arizona)

  • Pierre-A Blanche

    (University of Arizona)

  • Yushi Kaneda

    (University of Arizona)

  • Saikat Guha

    (University of Arizona)

  • Mark A. Neifeld

    (University of Arizona
    University of Arizona)

  • N. Peyghambarian

    (University of Arizona)

Abstract

Combinatorial optimization problems over large and complex systems have many applications in social networks, image processing, artificial intelligence, computational biology and a variety of other areas. Finding the optimized solution for such problems in general are usually in non-deterministic polynomial time (NP)-hard complexity class. Some NP-hard problems can be easily mapped to minimizing an Ising energy function. Here, we present an analog all-optical implementation of a coherent Ising machine (CIM) based on a network of injection-locked multicore fiber (MCF) lasers. The Zeeman terms and the mutual couplings appearing in the Ising Hamiltonians are implemented using spatial light modulators (SLMs). As a proof-of-principle, we demonstrate the use of optics to solve several Ising Hamiltonians for up to thirteen nodes. Overall, the average accuracy of the CIM to find the ground state energy was ~90% for 120 trials. The fundamental bottlenecks for the scalability and programmability of the presented CIM are discussed as well.

Suggested Citation

  • Masoud Babaeian & Dan T. Nguyen & Veysi Demir & Mehmetcan Akbulut & Pierre-A Blanche & Yushi Kaneda & Saikat Guha & Mark A. Neifeld & N. Peyghambarian, 2019. "A single shot coherent Ising machine based on a network of injection-locked multicore fiber lasers," Nature Communications, Nature, vol. 10(1), pages 1-11, December.
    • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-11548-4
    DOI: 10.1038/s41467-019-11548-4
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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.

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