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Adaptive meshing strategies for nanophotonics using a posteriori error estimation.

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    Adaptive mesh refinement speeds up nanophotonic device simulations by reducing computational cost and memory usage. Careful implementation is needed to avoid mesh propagation issues for successful application.

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    Area of Science:

    • Computational physics and engineering
    • Nanophotonics and optical device design
    • Numerical simulation methods

    Background:

    • Nanophotonic device complexity necessitates advanced simulation techniques.
    • Computational expense of traditional simulations hinders optimization and inverse design.
    • Finite-element method (FEM) is a common simulation approach.

    Purpose of the Study:

    • To investigate adaptive mesh refinement (AMR) for FEM simulations of nanophotonic devices.
    • To assess the efficiency and accuracy improvements offered by AMR.
    • To identify potential challenges in applying AMR to complex structures.

    Main Methods:

    • Utilized an a posteriori error estimation method for adaptive meshing.
    • Applied FEM simulations to complex three-dimensional nanophotonic structures.
    • Analyzed convergence rates and memory footprint with and without AMR.

    Main Results:

    • Adaptive meshing demonstrated faster convergence for complex 3D nanophotonic structures.
    • AMR resulted in a lower memory footprint compared to traditional meshing.
    • A potential mesh propagation effect was identified as a critical factor for successful AMR.

    Conclusions:

    • Adaptive mesh refinement is a viable strategy for accelerating nanophotonic device simulations.
    • AMR offers significant computational advantages in terms of speed and memory.
    • Careful handling of mesh propagation is crucial for reliable AMR implementation.