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

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

doi:10.23919/aces57841.2023.10114727

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

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

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

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.

Original language	English
Title of host publication	2023 International Applied Computational Electromagnetics Society Symposium (ACES)
Publisher	IEEE
ISBN (Electronic)	9781733509633
DOIs	https://doi.org/10.23919/aces57841.2023.10114727
Publication status	Published - 9 May 2023

Keywords

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

ASJC Scopus subject areas

Computational Mathematics
Instrumentation
Radiation
Computer Networks and Communications
Signal Processing

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10.23919/aces57841.2023.10114727

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title = "Mini-Max-Optimized Semi-analytical (MiMOSA) Approximation of Convoluted Susceptibility",

abstract = "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.",

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

author = "Prokopeva, {Ludmila J.} and Wallace Jaffray and Sarah Chowdhury and Karthik Pagadala and Marcello Ferrera and Kildishev, {Alexander V.}",

year = "2023",

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day = "9",

doi = "10.23919/aces57841.2023.10114727",

language = "English",

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T1 - Mini-Max-Optimized Semi-analytical (MiMOSA) Approximation of Convoluted Susceptibility

AU - Prokopeva, Ludmila J.

AU - Jaffray, Wallace

AU - Chowdhury, Sarah

AU - Pagadala, Karthik

AU - Ferrera, Marcello

AU - Kildishev, Alexander V.

PY - 2023/5/9

Y1 - 2023/5/9

N2 - 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.

AB - 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.

KW - Gaussian absorption

KW - Lorentz-Gaussian convolution

KW - Voight lineshape

KW - finite difference time domain

KW - generalized dispersive material (GDM)

KW - inhomogeneous broadening

KW - material dispersion

KW - minimax optimization

UR - http://www.scopus.com/inward/record.url?scp=85160010870&partnerID=8YFLogxK

U2 - 10.23919/aces57841.2023.10114727

DO - 10.23919/aces57841.2023.10114727

M3 - Conference contribution

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

PB - IEEE

ER -

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

Abstract

Keywords

ASJC Scopus subject areas

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