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Versatile manipulation of orbital angular momentum combs enabled by diffractive neural networks.

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    Researchers developed a diffractive neural network (DNN) to precisely control orbital angular momentum (OAM) combs. This versatile manipulation of OAM light opens new avenues for optical applications.

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    Area of Science:

    • Optics and Photonics
    • Quantum Optics
    • Information Optics

    Background:

    • Orbital angular momentum (OAM) of light, characterized by helical phase fronts, is crucial for classical and quantum optics.
    • OAM manipulation has advanced from single modes to complex superpositions like OAM combs, which have discrete, equispaced OAM spectra.

    Purpose of the Study:

    • To propose and demonstrate a versatile method for manipulating OAM combs.
    • To explore the potential of diffractive neural networks (DNNs) for advanced OAM light control.

    Main Methods:

    • Utilized a two-layer fully connected diffractive neural network (DNN).
    • Implemented four distinct categories of OAM comb manipulation and transformation.

    Main Results:

    • Achieved high accuracy (average 99.65%, lowest >99%) in OAM comb manipulation.
    • Demonstrated arithmetic, filtering, and arbitrary transformation capabilities for OAM combs.

    Conclusions:

    • The DNN approach offers versatile and accurate control over OAM combs.
    • This work may significantly advance OAM comb research and enable new applications.