Mini-Max-Optimized Semi-analytical (MiMOSA) Approximation of Convoluted Susceptibility

Ludmila J. Prokopeva,Wallace Jaffray,Sarah Chowdhury,Karthik Pagadala,Marcello Ferrera,Alexander V. Kildishev

2023 International Applied Computational Electromagnetics Society Symposium (ACES)（2023）

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摘要

We present a Mini-Max-Optimized Semi-analytical Approximation (MiMOSA) method to efficiently model the convolution type of dispersion in time-domain electromagnetic and multiphysics solvers. The method is based on an efficient (only 2 or 3 poles) and accurate minimax rational approximation. We discuss a representative case for this material dispersion class - disordered materials exhibiting inhomogeneous broadening with Voight absorption profiles. Accurate experimental-based modeling of disordered materials in the time domain was unavailable, and MiMOSA approximations fill this gap.

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关键词

finite difference time domain,generalized dispersive material (GDM),Gaussian absorption,Lorentz-Gaussian convolution,material dispersion,Voight lineshape,inhomogeneous broadening,minimax optimization

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