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Adaptive-sampling angular spectrum method with full utilization of space-bandwidth product.

Wenhui Zhang, Hao Zhang, Guofan Jin

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    This study introduces an adaptive-sampling angular spectrum method (ASM) to optimize diffraction calculations. It avoids zero padding, reducing computational load and improving sampling efficiency for wave propagation.

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    Area of Science:

    • Optics and Photonics
    • Computational Physics
    • Digital Signal Processing

    Background:

    • Convolution-based diffraction methods like Rayleigh-Sommerfeld and the angular spectrum method (ASM) often necessitate zero padding.
    • Zero padding is employed to prevent circular convolution errors but significantly increases computational complexity and sampling point wastage.

    Purpose of the Study:

    • To propose an adaptive-sampling ASM that eliminates the need for zero padding in diffraction calculations.
    • To enhance computational efficiency and optimize the utilization of sampling points in wave propagation simulations.

    Main Methods:

    • Analysis of sampling properties within the convolution process.
    • Development of an adaptive-sampling ASM that adjusts sampling parameters based on propagation distance.
    • Rearrangement of spatial frequency domain sampling points to satisfy transfer function sampling conditions.

    Main Results:

    • Successfully avoided circular convolution errors without employing zero padding.
    • Significantly reduced computational complexity compared to traditional methods.
    • Achieved full utilization of sampling points, maximizing the space-bandwidth product.

    Conclusions:

    • The adaptive-sampling ASM offers a computationally efficient and effective alternative for diffraction calculations.
    • This method optimizes resource utilization in wave propagation simulations.
    • It provides a significant advancement for numerical modeling in optics and photonics.