2018
DOI: 10.1016/j.jcp.2018.06.033
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Simulation of three-dimensional nanoscale light interaction with spatially dispersive metals using a high order curvilinear DGTD method

Abstract: In this work, we present and study a flexible and accurate numerical solver in the context of three-dimensional computational nanophotonics. More precisely, we focus on the propagation of electromagnetic waves through metallic media described by a non-local dispersive model. For this model, we propose a discretization based on a high-order Discontinuous Galerkin timedomain method, along with a low-storage Runge-Kutta time scheme of order four. The semidiscrete stability of the scheme is analyzed for classical … Show more

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Cited by 18 publications
(12 citation statements)
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“…1b-c. A more general implementation could be in principle obtained by employing more complex numerical schemes that allow curvilinear elements. [44][45][46] Such schemes, however, go beyond the scope of this work. In this letter, we neglect line-edge roughness and consider the apertures to be perfectly circular.…”
Section: Gap Roughnessmentioning
confidence: 99%
“…1b-c. A more general implementation could be in principle obtained by employing more complex numerical schemes that allow curvilinear elements. [44][45][46] Such schemes, however, go beyond the scope of this work. In this letter, we neglect line-edge roughness and consider the apertures to be perfectly circular.…”
Section: Gap Roughnessmentioning
confidence: 99%
“…The HDG method belongs to the class of discontinuous Galerkin (DG) methods, which are unstructured, high accurate, locally conservative, exhibit low dissipation and dispersion and are high-order, meaning the numerical error in the approximation can be made insensitive to the mesh discretization, as opposed to other finite-difference time-domain (FDTD) or finite element method (FEM) commercial solvers. For the aforementioned reasons, DG methods have been extensively used to simulate plasmonics phenomena [50][51][52][53][54]. The HDG method differs from other DG methods in the introduction of auxiliary variables defined on the faces of the discretization -also known as hybrid variables, hence the name hybridizable-, which enable the solution of smaller linear systems of equations and attain optimal convergence rates.…”
Section: Simulation Methodsmentioning
confidence: 99%
“…The HDG method differs from other DG methods in the introduction of auxiliary variables defined on the faces of the discretization -also known as hybrid variables, hence the name hybridizable-, which enable the solution of smaller linear systems of equations and attain optimal convergence rates. Thus, the HDG method is a strong candidate for solving extreme nanophotonics phenomena [44,45,52]. For a more thorough review on the HDG method and its implementation to the infinite slit problem, we refer the reader to Appendix A.…”
Section: Simulation Methodsmentioning
confidence: 99%
“…In order to estimate how precise our estimation of β could be with the grating setup, we proceed in the same fashion as for the geometric telemetry but we use a wavelength range of [550, 800] nm. Using DIOGENeS and DGTD [38], we find the β value which minimizes the distance between R and R meas . The geometric size of the structure, in combination with the very small effective wavelengths and the short interaction range of nonlocal effects, which is in the range of several nm at the metallodielectric interface, result in a computationally expensive procedure.…”
Section: Model Calibrationmentioning
confidence: 99%