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    Area of Science:

    • Astronomy and Astrophysics
    • Optical Engineering

    Background:

    • Ground-Layer Adaptive Optics (GLAO) is crucial for high-resolution solar imaging.
    • Current guide-star (GS) arrangement optimization is simulation-heavy and lacks prior design guidance.

    Purpose of the Study:

    • To develop an analytical framework for optimizing guide-star arrangements in solar GLAO systems.
    • To provide accurate prior optimization results independent of iterative simulations.

    Main Methods:

    • Analysis of GLAO wavefront sensing in the spatial frequency domain.
    • Construction of a filter to optimize detection of conformal aberrations.
    • Development of an analytical framework for guide-star arrangement optimization.

    Main Results:

    • An analytical framework for guide-star arrangement optimization was successfully developed.
    • The framework provides accurate prior optimization results for any guide-star configuration.
    • The method's correctness was validated against Monte Carlo simulations.

    Conclusions:

    • The new analytical framework significantly improves the efficiency of solar GLAO system design.
    • This method offers practical utility for optimizing solar GLAO performance.
    • It reduces reliance on time-consuming iterative simulations for system design.