A single shot coherent Ising machine based on a network of injection-locked multicore fiber lasers
Final Published Version
Nguyen, Dan T
Neifeld, Mark A
AffiliationUniv Arizona, Ctr Opt Sci
Univ Arizona, Dept Phys
Univ Arizona, Dept Elect & Comp Engn
MetadataShow full item record
PublisherNATURE PUBLISHING GROUP
CitationBabaeian, M., Nguyen, D. T., Demir, V., Akbulut, M., Blanche, P. A., Kaneda, Y., ... & Peyghambarian, N. (2019). A single shot coherent Ising machine based on a network of injection-locked multicore fiber lasers. Nature communications, 10(1), 1-11.
RightsCopyright © The Author(s) 2019. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License.
Collection InformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at firstname.lastname@example.org.
AbstractCombinatorial 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 lsing energy function. Here, we present an analog all-optical implementation of a coherent lsing 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 similar to 90% for 120 trials. The fundamental bottlenecks for the scalability and programmability of the presented CIM are discussed as well.
NoteOpen access journal
VersionFinal published version
SponsorsOffice of Naval Research (ONR) MURI program on Optical Computing [N00014-14-1-0505]; NSF ERC CIAN [EEC-0812072]; State of Arizona TRIF
Except where otherwise noted, this item's license is described as Copyright © The Author(s) 2019. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License.
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