Modelling self-similar parabolic pulses in optical fibres with a neural network

Modelling self-similar parabolic pulses in optical fibres with a neural network

We expand our previous analysis of nonlinear pulse shaping in optical fibres using machine learning [Opt. Laser Technol., 131 (2020) 106439] to the case of pulse propagation in the presence of gain/loss, with a special focus on the generation of self-similar parabolic pulses. We use a supervised fee...

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Veröffentlicht in:Results in optics 2021-05, Vol.3, p.100066, Article 100066
Hauptverfasser: Boscolo, Sonia, Dudley, John M., Finot, Christophe
Format: Artikel
Sprache:eng
Schlagworte:
Neural networks
Nonlinear propagation
Optical fibers
Optics
Parabolic pulse
Physics
Pulse shaping
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Zusammenfassung:We expand our previous analysis of nonlinear pulse shaping in optical fibres using machine learning [Opt. Laser Technol., 131 (2020) 106439] to the case of pulse propagation in the presence of gain/loss, with a special focus on the generation of self-similar parabolic pulses. We use a supervised feedforward neural network paradigm to solve the direct and inverse problems relating to the pulse shaping, bypassing the need for direct numerical solution of the governing propagation model.
ISSN:2666-9501
2666-9501
DOI:10.1016/j.rio.2021.100066