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All optical on-chip nonlinear activation functions for multi-wavelength computation.

Gongyu Xia, Jiacheng Liu, Pingyu Zhu

    Optics Express
    |June 14, 2025
    PubMed
    Summary
    This summary is machine-generated.

    Researchers developed an all-optical nonlinear activation unit for multi-wavelength computing. This silicon-based device mimics neural network functions, achieving 98.84% accuracy on the MNIST dataset for optical computing advancements.

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    Area of Science:

    • Photonics
    • Optical Computing
    • Materials Science

    Background:

    • Optical neural networks require efficient nonlinear activation functions.
    • Existing solutions often face limitations in multi-wavelength systems.
    • Silicon photonics offers a promising platform for integrated optical devices.

    Purpose of the Study:

    • To propose and experimentally validate an all-optical on-chip nonlinear activation function unit.
    • To leverage silicon's two-photon absorption and thermo-optic effects for optical nonlinearity.
    • To demonstrate the unit's capability in multi-wavelength computing and optical neural networks.

    Main Methods:

    • Device design and parameter optimization using simulation.
    • Fabrication of the proposed silicon-based optical unit.
    • Experimental testing to obtain the unit's response curve.
    • Numerical simulations for performance evaluation in classification tasks.

    Main Results:

    • Achieved a CELU-like nonlinear response curve experimentally.
    • Demonstrated high recognition accuracy of 98.84% on the MNIST dataset.
    • Validated the unit's effectiveness for optical neural network applications.

    Conclusions:

    • The developed all-optical unit effectively implements a nonlinear activation function on-chip.
    • This work bridges a critical gap for multi-wavelength optical computing.
    • The findings contribute to the advancement of efficient and powerful optical computing platforms.