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

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.

Mots clés: photonic nanostructures; nano plasmonics; nano-optics; electrodynamical simulations; coupled dipoles approximation; green dyadic method

Domaines: Systèmes mésoscopiques et effet Hall quantique [cond-mat.mes-hall]; Physique Numérique [physics.comp-ph]; Optique [physics.optics]

Peter Wiecha. pyGDM—A python toolkit for full-field electro-dynamical simulations and evolutionary optimization of nanostructures. Computer Physics Communications, 2018, 233, pp.167-192. ⟨10.1016/j.cpc.2018.06.017⟩. ⟨hal-01835860⟩