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Article Dans Une Revue Optics Letters Année : 2022

Phase space topology of four-wave mixing reconstructed by a neural network

Résumé

The dynamics of ideal four-wave mixing in optical fiber is reconstructed by taking advantage of the combination of experimental measurements with supervised machine learning strategies. The training data consist of power-dependent spectral phase and amplitude recorded at the output of a short segment of fiber. The neural network is able to accurately predict the nonlinear dynamics over tens of kilometers, and to retrieve the main features of the phase space topology including multiple Fermi-Pasta-Ulam recurrence cycles and the system separatrix boundary.
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Dates et versions

hal-03716846 , version 1 (07-07-2022)

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Anastasiia Sheveleva, Pierre Colman, John M Dudley, Christophe Finot. Phase space topology of four-wave mixing reconstructed by a neural network. Optics Letters, 2022, 47 (24), pp.6317-6320. ⟨10.1364/OL.472039⟩. ⟨hal-03716846⟩
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