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All-optical non-linear activation function for neuromorphic photonic computing using semiconductor Fano lasers.

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    Semiconductor Fano lasers can create all-optical non-linear activation functions for neuromorphic photonic computing. This technology enables high-speed optical pulse generation with significant on/off state suppression.

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    Area of Science:

    • Photonics
    • Optical Computing
    • Materials Science

    Background:

    • Neuromorphic photonic computing aims to mimic the brain's structure and function using light.
    • Developing efficient all-optical non-linear activation functions is crucial for advancing this field.
    • Semiconductor Fano lasers offer unique optical properties that could be leveraged for such functions.

    Purpose of the Study:

    • To predict the feasibility of using semiconductor Fano lasers for all-optical non-linear activation functions.
    • To investigate the potential of optical control of Fano mirrors in laser design.
    • To analyze key performance metrics including threshold energy, repetition rate, and signal suppression.

    Main Methods:

    • Theoretical prediction and numerical simulations were employed.
    • The study focused on exploiting optical control of a Fano mirror within a semiconductor laser.
    • Performance parameters such as switching threshold energy, extinction ratio, and refractory period were estimated and compared.

    Main Results:

    • Semiconductor Fano lasers can function as all-optical non-linear activation units.
    • The proposed laser design allows for optical pulse generation with low threshold energy.
    • High gigahertz repetition rates and significant on/off state suppression (orders of magnitude) were predicted.

    Conclusions:

    • Semiconductor Fano lasers show strong potential for realizing all-optical non-linear activation functions.
    • The optical control of Fano mirrors is a viable mechanism for achieving desired laser characteristics.
    • The predicted performance metrics align well between analytical estimates and numerical results, validating the approach.