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Integrated photonic reservoir computing based on hierarchical time-multiplexing structure.

Hong Zhang, Xue Feng, Boxun Li

    Optics Express
    |January 22, 2015
    PubMed
    Summary
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    This study introduces a novel photonic reservoir computing (RC) system using hierarchical time-multiplexing for faster, larger-scale computation. The advanced design achieves superior performance in signal classification and chaotic time series prediction.

    Area of Science:

    • Photonics
    • Optical Computing
    • Artificial Intelligence

    Background:

    • Reservoir computing (RC) offers a promising approach for complex computations.
    • Existing photonic RC systems face limitations in scalability and processing speed.
    • Time-multiplexing is a key technique for enhancing RC system capacity.

    Purpose of the Study:

    • To propose and numerically simulate an integrated photonic reservoir computing system.
    • To implement a hierarchical time-multiplexing structure for improved RC performance.
    • To demonstrate the system's effectiveness for signal classification and time series prediction.

    Main Methods:

    • Utilizing a micro-ring array (MRA) for time-delayed photonic computation.
    • Implementing a secondary time-multiplexing stage with a multi-mode interference (MMI) splitter and delay line array.

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  • Conducting numerical simulations to evaluate system performance and error rates.

    • Main Results:

    • The proposed hierarchical time-multiplexing structure enables a large reservoir size with high processing speeds.
    • Achieved a normalized mean square error of 0.5% for signal classification tasks.
    • Achieved a normalized mean square error of 2.7% for chaotic time series prediction.
    • Demonstrated a high sample rate of 1.3 Gbps.

    Conclusions:

    • The integrated photonic RC system with hierarchical time-multiplexing significantly outperforms previous designs.
    • The proposed architecture effectively balances reservoir size and processing speed.
    • This approach holds potential for advanced optical computing applications.