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A nonlinear least squares framework for periodic grating identification with a high-order perturbation of surfaces implementation

机译:非线性最小二乘框架,用于周期性光栅识别以及表面的高阶扰动实现

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The scattering of linear electromagnetic waves by a layered structure is a central model in many problems of engineering interest. In this contribution, we focus on the interaction of visible and near-visible radiation with periodic structures on the micron or nanometer scales which are relevant for many applications in nanoplasmonics. The fabrication of such structures is extremely difficult and costly, and even the most sophisticated laboratories have difficulty measuring the dimensions of gratings they have constructed. We present a new, extremely rapid and robust, identification algorithm for providing precisely this information. It is built upon a Nonlinear Least Squares framework, and implemented with a High-Order Perturbation of Surfaces methodology which is orders of magnitude faster than volumetric solvers, while outperforming surface methods (such as Boundary Integral Methods) for the geometries we consider here. In addition to a full derivation and specification of the algorithm, we also support our claims with a number of illustrative simulations. (C) 2019 Published by Elsevier B.V. on behalf of IMACS.
机译:分层结构对线性电磁波的散射是许多工程关注问题的中心模型。在这项贡献中,我们专注于可见光和近可见光辐射与微米或纳米尺度上周期性结构的相互作用,这与纳米等离子体技术中的许多应用有关。这种结构的制造极其困难且成本很高,即使是最先进的实验室也难以测量其所构造的光栅的尺寸。我们提出了一种新的,极其快速且健壮的识别算法,可精确地提供此信息。它建立在非线性最小二乘框架上,并使用高阶表面扰动方法实施,该方法比体积求解器快几个数量级,而我们在这里考虑的几何图形的表现优于表面方法(例如边界积分方法)。除了对算法的完整推导和说明之外,我们还通过许多示例性仿真来支持我们的主张。 (C)2019由Elsevier B.V.代表IMACS发布。

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