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Turbulence aberration correction for vector vortex beams using deep neural networks on experimental data.

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    Deep learning corrects atmospheric distortion in vector vortex beams (VVB), improving light mode purity. This adaptive optics system enhances VVB for applications like communication and imaging.

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    Area of Science:

    • Optics and Photonics
    • Artificial Intelligence in Optics

    Background:

    • Vector vortex beams (VVB) feature coupled polarization and orbital angular momentum (OAM), offering unique light field properties.
    • Atmospheric turbulence causes distortion, limiting practical applications of VVBs in communication and imaging.

    Purpose of the Study:

    • To develop and demonstrate a deep learning-based adaptive optics system for compensating atmospheric turbulence aberrations in VVBs.
    • To improve the phase distribution and mode purity of distorted VVBs.

    Main Methods:

    • A convolutional neural network (CNN) model, termed Turbulence Aberration Correction CNN (TACCNN), was designed to learn the mapping between distorted VVB intensity profiles and turbulence-induced phase aberrations.
    • The TACCNN model was trained using supervised learning with experimental data, focusing on aberrations generated by the first 20 Zernike modes.

    Main Results:

    • The TACCNN model successfully compensated for turbulence aberrations in VVBs, achieving rapid and accurate corrections.
    • Experimental results demonstrated a significant improvement in VVB mode purity from 19% to 70% under turbulence strength D/r0 = 5.28, with a correction time of 100 ms.
    • The system effectively compensated for both spatial modes and light intensity distribution under varying atmospheric turbulence conditions.

    Conclusions:

    • Deep learning-based adaptive optics offers a viable solution for overcoming atmospheric distortion challenges in VVB propagation.
    • The developed TACCNN system enhances VVB mode purity and spatial characteristics, paving the way for robust VVB applications in free-space optical communication and imaging.