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    This study introduces a new optimization scheme for broadband mode converters, crucial for high-capacity optical communications. The method achieves high-purity mode conversion with improved consistency across a wider bandwidth.

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    Area of Science:

    • Optical engineering
    • Photonics
    • Telecommunications

    Background:

    • Mode-division multiplexing (MDM) is vital for ultra-high-capacity optical systems.
    • Broadband mode converters are essential components in hybrid multiplexing systems for optical chips, fibers, and free-space optical communication (FSOC).
    • Existing diffractive neural network (DNN) based mode converters often suffer from narrow bandwidth operation and inconsistent output mode purity.

    Purpose of the Study:

    • To propose and demonstrate an optimization scheme for achieving broadband, high-purity mode conversion.
    • To improve the consistency of output modes across the entire operational bandwidth compared to existing methods.
    • To realize efficient mode conversion between perfect vortex beams and Gaussian beams over a significant bandwidth.

    Main Methods:

    • Development of a novel optimization scheme for broadband mode converters.
    • Utilizing multi-plane cascaded diffractive neural networks (DNNs).
    • Experimental realization of mode conversion within a 30 nm bandwidth centered at 1550 nm.

    Main Results:

    • Successful mode conversion between seven perfect vortex beams and Gaussian beams.
    • Achieved average output field fidelities of 0.987 (right) and 0.971 (left).
    • Minimum output fidelities reached 0.958 (right) and 0.980 (left), demonstrating high purity and consistency.

    Conclusions:

    • The proposed optimization scheme enables broadband, high-purity mode conversion with enhanced consistency.
    • This advancement is critical for the development of next-generation optical interconnects and communication systems.
    • The demonstrated performance highlights the potential of DNN-based mode converters for practical applications.