pyGDM—A python toolkit for full-field electro-dynamical simulations and evolutionary optimization of nanostructures

Peter Wiecha 1
1 CEMES-NeO - Nano-Optique et Nanomatériaux pour l'optique
CEMES - Centre d'élaboration de matériaux et d'études structurales
Abstract : pyGDM is a python toolkit for electro-dynamical simulations in nano-optics based on the Green Dyadic Method (GDM). In contrast to most other coupled-dipole codes, pyGDM uses a generalized propagator, which allows to cost-efficiently solve large monochromatic problems such as polarization-resolved calculations or raster-scan simulations with a focused beam or a quantum-emitter probe. A further peculiarity of this software is the possibility to very easily solve 3D problems including a dielectric or metallic substrate. Furthermore, pyGDM includes tools to easily derive several physical quantities such as far-field patterns, extinction and scattering cross-section, the electric and magnetic near-field in the vicinity of the structure, the decay rate of quantum emitters and the LDOS or the heat deposited inside a nanoparticle. Finally, pyGDM provides a toolkit for efficient evolutionary optimization of nanoparticle geometries in order to maximize (or minimize) optical properties such as a scattering at selected resonance wavelengths.
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Peter Wiecha. pyGDM—A python toolkit for full-field electro-dynamical simulations and evolutionary optimization of nanostructures. Computer Physics Communications, Elsevier, In press, ⟨10.1016/j.cpc.2018.06.017⟩. ⟨hal-01835860⟩

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