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

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.

pyGDM是一款基于格林二阶方法（Green Dyadic Method，简称GDM）的纳米光学电动力学模拟的Python工具包。与大多数其他耦合偶极子代码不同，pyGDM采用了一种广义传播子，这使得能够高效地解决大型单色问题，例如偏振分辨计算或聚焦光束或量子发射器探针的扫描模拟。该软件的另一显著特点是能够轻松解决包括介电或金属衬底在内的三维问题。此外，pyGDM还包含一系列工具，可轻松推导出多个物理量，如远场模式、消光和散射截面、结构附近的电场和磁场近场、量子发射器的衰减率以及纳米粒子内部的LDOS或热量沉积。最后，pyGDM提供了一套工具，用于高效地进化优化纳米粒子几何形状，以最大化（或最小化）选定的共振波长的光学特性。