Integrated optoelectronic devices represents a fundamental building block of hardware accelerators for photonics neural networks. Nanophotonic electro-optic modulators and detectors have significant performance advantages in power efficiency, communication bandwidth, and parallelism compared to conventional free-space photonics. Here, we present strategies and experimental validations of novel high-performance nanophotonic opto-electronic devices, involving heterogeneous integration of emerging materials into silicon photonic integrated circuits to exploit new functionality and device-scaling laws for efficient and ultrafast modulators, detectors, and photonic nonvolatile memory. The optoelectronic implementations of neural networks are demonstrated which significantly extends the spectrum of information processing capabilities.


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    Titel :

    High-performance optoelectronics for integrated photonic neural networks


    Beteiligte:
    Thomaschewski, Martin (Autor:in) / Hu, Zibo (Autor:in) / Nouri, Behrouz Movahhed (Autor:in) / Gui, Yaliang (Autor:in) / Wang, Hao (Autor:in) / Altaleb, Salem (Autor:in) / Dalir, Hamed (Autor:in) / Sorger, Volker J. (Autor:in)

    Kongress:

    AI and Optical Data Sciences IV ; 2023 ; San Francisco,California,United States


    Erschienen in:

    Proc. SPIE ; 12438


    Erscheinungsdatum :

    2023-03-15





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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