Stochastic logic in biased coupled photonic probabilistic bits

Abstract Optical computing often employs tailor-made hardware to implement specific algorithms, trading generality for improved performance in key aspects like speed and power efficiency. An important computing approach that is still missing its corresponding optical hardware is probabilistic comput...

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Main Authors: Michael Horodynski, Charles Roques-Carmes, Yannick Salamin, Seou Choi, Jamison Sloan, Di Luo, Marin Soljačić
Format: Article
Language:English
Published: Nature Portfolio 2025-01-01
Series:Communications Physics
Online Access:https://doi.org/10.1038/s42005-025-01953-1
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author Michael Horodynski
Charles Roques-Carmes
Yannick Salamin
Seou Choi
Jamison Sloan
Di Luo
Marin Soljačić
author_facet Michael Horodynski
Charles Roques-Carmes
Yannick Salamin
Seou Choi
Jamison Sloan
Di Luo
Marin Soljačić
author_sort Michael Horodynski
collection DOAJ
description Abstract Optical computing often employs tailor-made hardware to implement specific algorithms, trading generality for improved performance in key aspects like speed and power efficiency. An important computing approach that is still missing its corresponding optical hardware is probabilistic computing, used e.g. for solving difficult combinatorial optimization problems. In this study, we propose an experimentally viable photonic approach to solve arbitrary probabilistic computing problems. Our method relies on the insight that coherent Ising machines composed of coupled and biased optical parametric oscillators can emulate stochastic logic. We demonstrate the feasibility of our approach by using numerical simulations equivalent to the full density matrix formulation of coupled optical parametric oscillators.
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institution Kabale University
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publishDate 2025-01-01
publisher Nature Portfolio
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spelling doaj-art-472f72fa828c40a894699b4855aaa9a62025-01-26T12:37:07ZengNature PortfolioCommunications Physics2399-36502025-01-01811610.1038/s42005-025-01953-1Stochastic logic in biased coupled photonic probabilistic bitsMichael Horodynski0Charles Roques-Carmes1Yannick Salamin2Seou Choi3Jamison Sloan4Di Luo5Marin Soljačić6Department of Physics, Massachusetts Institute of TechnologyE. L. Ginzton Laboratory, Stanford UniversityDepartment of Physics, Massachusetts Institute of TechnologyResearch Laboratory of Electronics, Massachusetts Institute of TechnologyResearch Laboratory of Electronics, Massachusetts Institute of TechnologyDepartment of Physics, Massachusetts Institute of TechnologyDepartment of Physics, Massachusetts Institute of TechnologyAbstract Optical computing often employs tailor-made hardware to implement specific algorithms, trading generality for improved performance in key aspects like speed and power efficiency. An important computing approach that is still missing its corresponding optical hardware is probabilistic computing, used e.g. for solving difficult combinatorial optimization problems. In this study, we propose an experimentally viable photonic approach to solve arbitrary probabilistic computing problems. Our method relies on the insight that coherent Ising machines composed of coupled and biased optical parametric oscillators can emulate stochastic logic. We demonstrate the feasibility of our approach by using numerical simulations equivalent to the full density matrix formulation of coupled optical parametric oscillators.https://doi.org/10.1038/s42005-025-01953-1
spellingShingle Michael Horodynski
Charles Roques-Carmes
Yannick Salamin
Seou Choi
Jamison Sloan
Di Luo
Marin Soljačić
Stochastic logic in biased coupled photonic probabilistic bits
Communications Physics
title Stochastic logic in biased coupled photonic probabilistic bits
title_full Stochastic logic in biased coupled photonic probabilistic bits
title_fullStr Stochastic logic in biased coupled photonic probabilistic bits
title_full_unstemmed Stochastic logic in biased coupled photonic probabilistic bits
title_short Stochastic logic in biased coupled photonic probabilistic bits
title_sort stochastic logic in biased coupled photonic probabilistic bits
url https://doi.org/10.1038/s42005-025-01953-1
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