Heuristic recurrent algorithms for photonic Ising machines
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s41467-019-14096-z.pdf
Description
Published version
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1.01 MB
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Unknown
Checksum (MD5)
22c867d9cb85485bf74bc63f103c4c3b
Author(s)
Roques-Carmes, Charles
Shen, Yichen
Zanoci, Cristian
Prabhu, Mihika
Atieh, Fadi
Jing, Li
Dubcek, Tena
Mao, Chenkai
Johnson, Miles R
Ceperic, Vladimir
Date Issued
2020
Journal
Nature Communications
Publisher
Springer Science and Business Media LLC
Version
Final published version
Abstract
© 2020, The Author(s). The inability of conventional electronic architectures to efficiently solve large combinatorial problems motivates the development of novel computational hardware. There has been much effort toward developing application-specific hardware across many different fields of engineering, such as integrated circuits, memristors, and photonics. However, unleashing the potential of such architectures requires the development of algorithms which optimally exploit their fundamental properties. Here, we present the Photonic Recurrent Ising Sampler (PRIS), a heuristic method tailored for parallel architectures allowing fast and efficient sampling from distributions of arbitrary Ising problems. Since the PRIS relies on vector-to-fixed matrix multiplications, we suggest the implementation of the PRIS in photonic parallel networks, which realize these operations at an unprecedented speed. The PRIS provides sample solutions to the ground state of Ising models, by converging in probability to their associated Gibbs distribution. The PRIS also relies on intrinsic dynamic noise and eigenvalue dropout to find ground states more efficiently. Our work suggests speedups in heuristic methods via photonic implementations of the PRIS.
MIT Department
Massachusetts Institute of Technology. Research Laboratory of Electronics
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Department of Physics
Massachusetts Institute of Technology. Department of Mathematics
Massachusetts Institute of Technology. Institute for Soldier Nanotechnologies
Terms of Use
Creative Commons Attribution 4.0 International license
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DOI of Published Version
https://doi.org/10.1038/S41467-019-14096-Z
