Particle swarm optimization hyperparameters tuning for physical-model fitting of VCSEL measurements

Andrea Marchisio; Enrico Ghillino; Vittorio Curri; Andrea Carena; Paolo Bardella

doi:10.1117/12.3002576

13 March 2024 Particle swarm optimization hyperparameters tuning for physical-model fitting of VCSEL measurements

Andrea Marchisio, Enrico Ghillino, Vittorio Curri, Andrea Carena, Paolo Bardella

Proceedings Volume 12904, Vertical-Cavity Surface-Emitting Lasers XXVIII; 129040N (2024) https://doi.org/10.1117/12.3002576
Event: SPIE OPTO, 2024, San Francisco, California, United States

Conference Poster

Abstract

We propose a Particle Swarm Optimization (PSO) algorithm for the extraction of Vertical-Cavity Surface-Emitting Laser (VCSEL) parameters compatible with a rate equation based model that takes into account the thermal effects. PSO is an evolutionary algorithm that drastically reduces the computational cost and time with respect to traditional brute-force approaches, thanks to the "swarm intelligence" of the agents of the optimization (called "particles"). With an optimal choice of the hyperparameters of the algorithm, the method is shown to predict parameters that accurately reproduce the non-linear behavior of the device, as well as its complicated thermal effects.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Andrea Marchisio, Enrico Ghillino, Vittorio Curri, Andrea Carena, and Paolo Bardella "Particle swarm optimization hyperparameters tuning for physical-model fitting of VCSEL measurements", Proc. SPIE 12904, Vertical-Cavity Surface-Emitting Lasers XXVIII, 129040N (13 March 2024); https://doi.org/10.1117/12.3002576

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