Machine Learning Assisted Extraction of Vertical Cavity Surface Emitting Lasers Parameters

We propose a machine learning-based framework to extract circuit-level VCSEL model parameters. The proposed approach predicts the parameters exploiting the light-current curve and small-signal modulation responses with two steps at constant and variable temperature, respectively. Promising results are achieved in terms of relative prediction error.