A Parallel Block Preconditioner-Based VIE-FFT Algorithm for Modeling the Electromagnetic Response From Nanostructures
The superior ability of nanostructures to manipulate light has propelled extensive applications in nanoelectromagnetic components and devices. Computational electromagnetics plays a critical role in characterizing and optimizing the nanostructures. In this work, a parallel block preconditioner-based...
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Veröffentlicht in: | IEEE transactions on antennas and propagation 2024-01, Vol.72 (1), p.1051-1056 |
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Sprache: | eng |
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Zusammenfassung: | The superior ability of nanostructures to manipulate light has propelled extensive applications in nanoelectromagnetic components and devices. Computational electromagnetics plays a critical role in characterizing and optimizing the nanostructures. In this work, a parallel block preconditioner-based volume integral equation (VIE)-fast Fourier transform (FFT) algorithm is proposed to model the electromagnetic response from representative nanostructures. The VIE using uniform Cartesian grids is first built, and then the entire volumetric domain is partitioned into geometric subdomains based on the regularity and topology of the nanostructure. The block diagonal matrix is thus established, whose inverse matrix serves as a preconditioner for the original matrix equation. The resulting linear system is solved by the biconjugate gradient-stabilized (BiCGSTAB) method with different residual error tolerances in the inner and outer iteration processes and the FFT algorithm is used to accelerate the matrix-vector product (MVM) operations throughout. Furthermore, because of the independence between the inner processes of solving block matrix equations, the OpenMP framework is employed to execute the parallel operations. Numerical experiments indicate that the proposed method is effective and reduces both the iteration number and the computational time significantly for representative nanoelectromagnetic problems like the dielectric focusing metasurfaces and the plasmonic solar cells. |
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ISSN: | 0018-926X 1558-2221 |
DOI: | 10.1109/TAP.2023.3331512 |