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18 June 2024 Machine learning applications to nonlinear fiber-optics systems
Goëry Genty
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Proceedings Volume PC13017, Machine Learning in Photonics; PC1301703 (2024) https://doi.org/10.1117/12.3017628
Event: SPIE Photonics Europe, 2024, Strasbourg, France
Abstract
We will review our work in the field of smart ultrafast photonics where machine-learning algorithms are combined with nonlinear optical systems allowing for optimized performance and control. In particular, we will show how the techniques of machine learning can be efficiently exploited for the analysis of nonlinear instabilities; the prediction of complex supercontinuum generation dynamics with orders of magnitude increased computation speed when compared to conventional direct numerical integration; the optimized and precise control of the spectrum of broadband supercontinuum sources.
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Goëry Genty "Machine learning applications to nonlinear fiber-optics systems", Proc. SPIE PC13017, Machine Learning in Photonics, PC1301703 (18 June 2024); https://doi.org/10.1117/12.3017628
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KEYWORDS
Complex systems
Machine learning
Fiber optics
Nonlinear optimization
Supercontinuum generation
Photonics
Solitons
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