English

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

Computational Physics 2020-01-28 v2 Mesoscale and Nanoscale Physics Optics

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.

Keywords

Cite

@article{arxiv.1802.04071,
  title  = {pyGDM -- A python toolkit for full-field electro-dynamical simulations and evolutionary optimization of nanostructures},
  author = {Peter R. Wiecha},
  journal= {arXiv preprint arXiv:1802.04071},
  year   = {2020}
}

Comments

32 pages, 26 figures; python module in ancillary files. Online documentation available at https://wiechapeter.gitlab.io/pyGDM2-doc/

R2 v1 2026-06-23T00:19:17.280Z