2018
DOI: 10.1109/lpt.2018.2828167
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Finite-Difference Complex-Frequency-Domain Method for Optical and Plasmonic Analyses

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Cited by 21 publications
(19 citation statements)
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“…The incident waveform is a modulated Gaussian pulse, which is generally used in time domain solvers. Because the Laplace transform of the Gaussian type of pulses cannot be defined, we derived the pseudo-Gaussian pulse [19]. The center wavelength of the modulated Gaussian pulse is 444 nm, which is the plasmon resonance wavelength.…”
Section: Reference Solutionsmentioning
confidence: 99%
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“…The incident waveform is a modulated Gaussian pulse, which is generally used in time domain solvers. Because the Laplace transform of the Gaussian type of pulses cannot be defined, we derived the pseudo-Gaussian pulse [19]. The center wavelength of the modulated Gaussian pulse is 444 nm, which is the plasmon resonance wavelength.…”
Section: Reference Solutionsmentioning
confidence: 99%
“…The radius a of the cylinder is 100 nm, and the incident wave is assumed to be a plane wave. The waveform is a pseudo-Gaussian pulse [19],…”
Section: A Solution For a Perfect Electric Conducting Cylindermentioning
confidence: 99%
“…To perform an inverse Laplace transform, many numerical implementations have been proposed [6]. The fast inverse Laplace transform (FILT) is an easy and concise implementation [7] that has been successfully applied to practical EM analyses for plasmonic antennas [8], ground-penetrating radar [9], transmission lines [10], biological media [11], low-frequency issues, and problems related to DC components [12,13,14]. FILT can obtain the time-domain response independently at an arbitrary single time; therefore, it is convenient for performing parallel computations.…”
Section: Introductionmentioning
confidence: 99%
“…We recently developed a novel technique for conducting both time-and frequency-domain analyses; specifically, we combined FILT with the finite-difference complexfrequency-domain (FDCFD) method [12] for the near-field analysis of plasmonic objects. We also developed a time-division algorithm for the finite-difference time-domain (FDTD) technique [15].…”
Section: Introductionmentioning
confidence: 99%
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