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首页> 外文期刊>Journal of Scientific Computing >Computing Extremal Eigenvalues for Three-Dimensional Photonic Crystals with Wave Vectors Near the Brillouin Zone Center
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Computing Extremal Eigenvalues for Three-Dimensional Photonic Crystals with Wave Vectors Near the Brillouin Zone Center

机译:在布里渊区中心附近通过波矢计算三维光子晶体的极值特征值

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Abstract The band structures of three-dimensional photonic crystals can be determined numerically by solving a sequence of generalized eigenvalue problems. However, not all of the spectral structures of these eigenvalue problems are well-understood, and not all of these eigenvalue problems can be solved efficiently. This article focuses on the eigenvalue problems corresponding to wave vectors that are close to the center of the Brillouin zone of a three dimensional, simple cubic photonic crystal. For these eigenvalue problems, there are (i) many zero eigenvalues, (ii) a couple of near-zero eigenvalues, and (iii) several larger eigenvalues. As the desired eigenvalues are the smallest positive eigenvalues, these particular spectral structures prevent regular eigenvalue solvers from efficiently computing the desired eigenvalues. We study these eigenvalue problems from the perspective of both theory and computation. On the theoretical side, the structures of the null spaces are analyzed to explicitly determine the number of zero eigenvalues of the target eigenvalue problems. On the computational side, the Krylov-Schur and Jacobi-Davidson methods are used to compute the smallest, positive, interior eigenvalues that are of interest. Intensive numerical experiments disclose how the shift values, conditioning numbers, and initial vectors affect the performance of the tested eigenvalue solvers and suggest the most efficient eigenvalue solvers.
机译:摘要通过求解一系列广义特征值问题,可以数值确定三维光子晶体的能带结构。但是,并不是所有这些特征值问题的频谱结构都被很好地理解,并且并非所有这些特征值问题都可以有效地解决。本文重点研究与三维矢量简单立方光子晶体的布里渊区中心附近的波矢相对应的特征值问题。对于这些特征值问题,有(i)许多零特征值,(ii)几个接近零的特征值,以及(iii)一些较大的特征值。由于期望特征值是最小的正特征值,因此这些特定的频谱结构会阻止常规特征值求解器有效地计算期望特征值。我们从理论和计算的角度研究这些特征值问题。从理论上讲,分析零空间的结构以明确确定目标特征值问题的零特征值数量。在计算方面,Krylov-Schur和Jacobi-Davidson方法用于计算感兴趣的最小的正内部特征值。大量的数值实验揭示了位移值,条件数和初始向量如何影响测试的特征值求解器的性能,并提出了最有效的特征值求解器。

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