[ThH1] Modelling and Monitoring

9:45 AM - 10:00 AM JST(12:45 AM - 1:00 AM UTC)

[ThH1-3] Physics-informed Machine Learning for Modeling Dual-polarization Single-mode Fiber Transmission with Statistical Polarization Rotation

○Keisho Yamamoto¹, Takashi Taniguchi¹, Takumi Takahashi², Tadashi Wadayama³, Koji Igarashi¹ (1. Graduate School of Engineering Science, Osaka University (Japan), 2. Graduate School of Engineering, Osaka University (Japan), 3. Department of Computer Science and Software Engineering, Nagoya Institute of Technology (Japan))

Keywords:

Artificial intelligence and machine learning for optical transmission systems and subsystems

We employ physics-informed machine learning to investigate nonlinear fiber transmission. Our approach discerns difference between nonlinear factors of self-polarization modulation and cross-polarization modulation, elucidating applicable range of Manakov equation.