| Title: |
Applications of artificial intelligence to nonlinear fiber-optics |
| Authors: |
Genty, Goëry; Salmela, Lauri; Hary, Mathilde; Mabed, Mehdi; Ermolaev, Andrei; Dudley, John Michael |
| Contributors: |
Tampere University of Technology Tampere (TUT); Franche-Comté Électronique Mécanique, Thermique et Optique - Sciences et Technologies (UMR 6174) (FEMTO-ST); Université de Technologie de Belfort-Montbeliard (UTBM)-Ecole Nationale Supérieure de Mécanique et des Microtechniques (ENSMM)-Centre National de la Recherche Scientifique (CNRS)-Université de Franche-Comté (UFC); Université Bourgogne Franche-Comté COMUE (UBFC)-Université Bourgogne Franche-Comté COMUE (UBFC) |
| Source: |
SPIE Photonics West ; https://hal.science/hal-04258269 ; SPIE Photonics West, Jan 2023, San Francisco, California, United States |
| Publisher Information: |
CCSD |
| Publication Year: |
2023 |
| Collection: |
Université de Franche-Comté (UFC): HAL |
| Subject Terms: |
[PHYS.PHYS.PHYS-OPTICS]Physics [physics]/Physics [physics]/Optics [physics.optics] |
| Subject Geographic: |
San Francisco; California; United States |
| Description: |
International audience ; We review the use of machine learning techniques in ultrafast dynamics in fiber-optics systems. We discuss how neural networks can be used to correlate the spectral and temporal characteristics of dissipative soliton lasers and predict nonlinear dynamics in optical fibers for a wide range of input conditions. We also show how machine learning algorithm allow for optimizing supercontinuum generation. |
| Document Type: |
conference object |
| Language: |
English |
| Availability: |
https://hal.science/hal-04258269 |
| Accession Number: |
edsbas.DCAC0B97 |
| Database: |
BASE |