Particle swarm optimization-assisted approach for the extraction of VCSEL model parameters
Andrea Marchisio, Enrico Ghillino, Vittorio Curri, Andrea Carena, Paolo Bardella
Abstract
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.
Topics & Concepts
Particle swarm optimizationBenchmark (surveying)Nonlinear systemOpticsHyperparameterComputer scienceLevenberg–Marquardt algorithmModulation (music)LaserSIGNAL (programming language)Biological systemAlgorithmMaterials sciencePhysicsArtificial neural networkAcousticsArtificial intelligenceBiologyProgramming languageGeographyQuantum mechanicsGeodesySemiconductor Lasers and Optical DevicesPhotonic and Optical DevicesOptical Network Technologies