[ThD1] Hybrid Integration II and Advanced Materials

10:45 AM - 11:00 AM JST(1:45 AM - 2:00 AM UTC)

[ThD1-7] Unsupervised Machine Learning Study of GaAsBi Quantum Well Evolution After Annealing Based on Spatially Resolved micro-Photoluminescence Imaging.

○Lena N. Golubewa^1,2, Yaraslau Padrez¹, Aivaras Špokas^1,3, Andrea Zelioli¹, Aiste Štaupiene^1,3, Bronislovas Čechavičius¹, Evelina Dudutiene¹, Augustas Vaitkevičius^1,3, Renata Butkute^1,3 (1. State research institute Center for Physical Sciences and Technology (Lithuania), 2. Institute of Chemical Physics, Vilnius University (Lithuania), 3. Institute of Photonics and Nanotechnology, Vilnius University (Lithuania))

Keywords:

Artificial intelligence and machine learning for optical network design,control,and management,Semiconductor lasers,optical amplifiers,and light emitting diodes

Unsupervised machine learning-based analysis of spatially resolved photoluminescence images of GaAsBi quantum well structures reveals non-uniformity of optical properties of as-grown samples and their gradual modification and surface homogeneity increase after annealing at 700-750 °C.