Predicting frequency comb structure in nonlinear optical fibre using a neural network

Sonia Boscolo; John M. Dudley; Christophe Finot

doi:10.1051/epjconf/202328706019

Predicting frequency comb structure in nonlinear optical fibre using a neural network

Sonia Boscolo
, John M. Dudley
, Christophe Finot

Aston Institute of Photonic Technologies (AiPT)

Université de Franche-Comté
Institut FEMTO-ST
Université de Bourgogne Franche-Comté
Université de Bourgogne
Université Bourgogne Franche-Comté
University of Southampton
Université de Bourgogne Franche-Comté

Research output: Contribution to journal › Conference article › peer-review

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Abstract

We deploy a neural network to predict the spectro-temporal evolution of simple sinusoidal temporal modulations upon propagation in a nonlinear dispersive fibre. Thanks to the speed of the neural network, we can efficiently scan the input parameter space for the generation of on-demand frequency combs or the occurrence of substantial spectral/temporal focusing.

Original language	English
Article number	06019
Number of pages	2
Journal	EPJ Web of Conferences
Volume	287
DOIs	https://doi.org/10.1051/epjconf/202328706019
Publication status	Published - 18 Oct 2023
Event	EOS Annual Meeting (EOSAM 2023) - Dijon Exhibition and Convention Center, Dijon, France Duration: 11 Sept 2023 → 15 Sept 2023 https://www.europeanoptics.org/events/eos/eosam2023.html

Bibliographical note

© The Authors, published by EDP Sciences, 2023. This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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10.1051/epjconf/202328706019Licence: CC BY 4.0

epjconf_eosam2023_06019
© The Authors, published by EDP Sciences, 2023. This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Final published version, 1.58 MBLicence: CC BY 4.0

Cite this

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abstract = "We deploy a neural network to predict the spectro-temporal evolution of simple sinusoidal temporal modulations upon propagation in a nonlinear dispersive fibre. Thanks to the speed of the neural network, we can efficiently scan the input parameter space for the generation of on-demand frequency combs or the occurrence of substantial spectral/temporal focusing.",

author = "Sonia Boscolo and Dudley, \{John M.\} and Christophe Finot",

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AU - Boscolo, Sonia

AU - Dudley, John M.

AU - Finot, Christophe

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PY - 2023/10/18

Y1 - 2023/10/18

N2 - We deploy a neural network to predict the spectro-temporal evolution of simple sinusoidal temporal modulations upon propagation in a nonlinear dispersive fibre. Thanks to the speed of the neural network, we can efficiently scan the input parameter space for the generation of on-demand frequency combs or the occurrence of substantial spectral/temporal focusing.

AB - We deploy a neural network to predict the spectro-temporal evolution of simple sinusoidal temporal modulations upon propagation in a nonlinear dispersive fibre. Thanks to the speed of the neural network, we can efficiently scan the input parameter space for the generation of on-demand frequency combs or the occurrence of substantial spectral/temporal focusing.

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DO - 10.1051/epjconf/202328706019

M3 - Conference article

SN - 2100-014X

VL - 287

JO - EPJ Web of Conferences

JF - EPJ Web of Conferences

M1 - 06019

T2 - EOS Annual Meeting (EOSAM 2023)

Y2 - 11 September 2023 through 15 September 2023

ER -

Predicting frequency comb structure in nonlinear optical fibre using a neural network

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