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    Area of Science:

    • Computational Physics
    • Optical Engineering
    • Parallel Computing

    Background:

    • Atmospheric and adaptive optics simulations are crucial for various applications.
    • Existing simulation methods can be computationally intensive and time-consuming.
    • Efficient simulation techniques are needed to advance optical system design and analysis.

    Purpose of the Study:

    • To develop a novel parallel programming technique for atmospheric and adaptive optics simulations.
    • To design an efficient parallel propagation algorithm.
    • To create a modified spectral-phase method for generating 2D time-variant random fields.

    Main Methods:

    • Developed a parallel propagation algorithm.
    • Created a modified spectral-phase method for random field generation.
    • Utilized Intel MKL, IPP libraries, and NVIDIA CUDA technology for implementation.
    • Tested on a desktop system with Intel Core i7 CPU and NVIDIA GeForce GTX-960 GPU.

    Main Results:

    • The proposed algorithms demonstrate high speed and accuracy in simulations.
    • Successfully generated 2D time-variant random fields.
    • Analyzed temporal power spectra of Laguerre-Gaussian beam fluctuations as a practical example.
    • Achieved efficient performance leveraging parallel processing capabilities.

    Conclusions:

    • The developed parallel computing technique offers a fast and accurate solution for atmospheric and adaptive optics simulations.
    • The modified spectral-phase method is effective for generating complex random fields.
    • Implementation on modern hardware significantly accelerates simulation processes.