Particle swarm optimization-assisted approach for the extraction of VCSEL model parameters

We propose a direct particle swarm optimization (PSO) method for extracting the parameters of a physical model describing the behavior of vertical-cavity surface-emitting lasers (VCSELs), starting from the light-current (L-I) characteristics and the small signal modulation (S21) responses, at different currents and temperatures. With an optimal choice of hyperparameters of the algorithm, the method is able to predict parameters that accurately reproduce the behavior of the device. Its prediction capabilities are compared to those of two commonly used nonlinear optimizers (Interior Point and Levenberg–Marquardt), to benchmark its performances.