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Optica Publishing Group
  • Current Optics and Photonics
  • Vol. 8,
  • Issue 1,
  • pp. 80-85
  • (2024)

Deep Learning-based Extraction of Auger and FCA Coefficients in 850 nm GaAs/AlGaAs Laser Diodes

Open Access Open Access

Abstract

Numerical values of the Auger coefficient and the free carrier absorption (FCA) coefficient are extracted by applying deep neural networks (DNNs) to the L-I characteristics of 850 nm GaAs/AlGaAs laser diodes. Two elemental DNNs are used to extract each coefficient sequentially. The fidelity of the extracted values is established through meticulous correlation of L-I characteristics bridging the realms of simulations and measurements. The methodology presented in this paper offers a way to accurately extract the Auger and FCA coefficients, which were traditionally treated as fitting parameters. It is anticipated that this approach will be applicable to other types of opto-electronic devices as well.

© 2024 Optical Society of Korea

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