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Molecular Beam Mass Spectrometry With Tunable Vacuum Ultraviolet VUV Synchrotron Radiation
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A generalized expression for accelerating beamlet decomposition simulations.

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    This study accelerates Gaussian beamlet decomposition (GBD) for optical system simulation. The new method significantly enhances computational efficiency, enabling faster parameter optimization for complex optical phenomena.

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    Area of Science:

    • Optics and Photonics
    • Computational Physics

    Background:

    • Fourier transform-based paraxial diffraction modeling is common for optical systems.
    • Non-paraxial systems require hybrid propagation physics, leading to beamlet decomposition algorithms like Gaussian beamlet decomposition (GBD).

    Purpose of the Study:

    • To enhance the computational efficiency of the GBD algorithm.
    • To develop an accelerated GBD method for parameter-space searching.

    Main Methods:

    • Derived an alternative GBD expression using analytical propagation of beamlets to tilted planes.
    • Employed the accelerated algorithm for parameter-space search to construct the analytical Airy function.

    Main Results:

    • The new GBD algorithm achieved a 34x speedup on CPUs and a 67,513x speedup on GPUs compared to the previous algorithm.
    • Successfully used the accelerated method to find optimal GBD parameters for Airy function construction.

    Conclusions:

    • The derived GBD algorithm offers substantial computational speedups for optical system simulations.
    • This acceleration facilitates efficient parameter optimization and complex optical function synthesis.