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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.
Andrei V. Ermolaev,Christophe Finot,Goëry Genty, andJohn 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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Andrei V. Ermolaev, Christophe Finot, Goëry Genty, 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