Automatized convergence of optoelectronic simulations using active machine learning

A fundamental problem of optoelectronic simulations is to achieve convergence. We use statistical analysis and machine learning to effectively guide the selection of the next device to be examined based upon the expected convergence of the simulation. This active learning strategy rapidly constructs a model that predicts Poisson-Schrdinger simulations of devices and that simultaneously produces fully converged simulations.