Identifying dominant physical interactions in nonlinear fibre optics using machine learning

Andrei V. Ermolaev; Christophe Finot; Goëry Genty; John M. Dudley

doi:10.1117/12.3016777

20 June 2024 Identifying dominant physical interactions in nonlinear fibre optics using machine learning

Andrei V. Ermolaev, Christophe Finot, Goëry Genty, John M. Dudley

Proceedings Volume PC13004, Nonlinear Optics and its Applications 2024; PC1300406 (2024) https://doi.org/10.1117/12.3016777
Event: SPIE Photonics Europe, 2024, Strasbourg, France

Abstract

We apply the machine learning technique of dominant balance analysis to study nonlinear and dispersive pulse propagation in optical fibre. We show results for different cases including: the emergence of modulation instability from noise; fundamental and higher-order soliton propagation; soliton-dispersive wave generation; Raman soliton and supercontinuum dynamics; optical wavebreaking; the generation of Riemann wave shocks. For all cases, we show how we can automatically distinguish regions of dominant interactions where different nonlinear and dispersive terms combine to drive the propagation dynamics.

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

Citation Download Citation

Andrei V. Ermolaev, Christophe Finot, Goëry Genty, and John M. Dudley "Identifying dominant physical interactions in nonlinear fibre optics using machine learning", Proc. SPIE PC13004, Nonlinear Optics and its Applications 2024, PC1300406 (20 June 2024); https://doi.org/10.1117/12.3016777

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