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Using multidimensional speckle dynamics for high-speed, large-scale, parallel photonic computing.

Satoshi Sunada, Kazutaka Kanno, Atsushi Uchida

    Optics Express
    |October 29, 2020
    PubMed
    Summary
    This summary is machine-generated.

    Researchers developed a novel photonic computing approach using multimode fiber speckle dynamics for high-speed data processing. This method enables fast, nonlinear information processing and multitasking, paving the way for advanced computing hardware.

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    Area of Science:

    • Photonics
    • Machine Learning
    • Optical Computing

    Background:

    • Increasing data processing demands necessitate innovative machine learning concepts and hardware.
    • Physical reservoir computing leverages physical systems for high-dimensional, nonlinear information processing.

    Purpose of the Study:

    • To propose and demonstrate the use of multidimensional speckle dynamics in multimode fibers for high-speed information processing.
    • To explore the potential of this approach for nonlinear time-dependent computations.

    Main Methods:

    • Input information is mapped into spatial, frequency, and time domains using optical phase modulation.
    • Speckle dynamics in multimode fibers are utilized for high-dimensional, nonlinear information mapping.
    • A reservoir-computing-like approach is applied to the speckle dynamics for data processing.

    Main Results:

    • Experimental demonstration of chaotic time-series prediction at 12.5 Gigasamples per second.
    • Successful nonlinear time-dependent information processing at high rates.
    • Demonstration of multitasking capabilities due to the passive nature of multimode fibers.

    Conclusions:

    • Multidimensional speckle dynamics in multimode fibers offer a novel approach for photonic computing.
    • This method enables parallel, high-speed, and large-scale information processing.
    • The findings pave the way for next-generation optical computing hardware.