| Title: |
New insights, new experiments, and new approaches to computation: the many synergies between machine learning and nonlinear fibre optics. |
| Authors: |
Dudley, John Michael; Ermolaev, Andrei; Hary, Mathilde; Leybov, Ley; Ryczkowski, Piotr; Skalli, Anas; Brunner, Daniel; Meng, Fanchao; Finot, Christophe; Genty, Goëry |
| Contributors: |
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); Institut universitaire de France (IUF); Ministère de l'Education nationale, de l’Enseignement supérieur et de la Recherche (M.E.N.E.S.R.); Tampere University of Technology Tampere (TUT); College of Electronic Science and Engineering; National University of Defense Technology China; Laboratoire Interdisciplinaire Carnot de Bourgogne (ICB); Université de Technologie de Belfort-Montbeliard (UTBM)-Centre National de la Recherche Scientifique (CNRS)-Université Bourgogne Europe (UBE); ANR-20-CE30-0004,OPTIMAL,Optimisation des sources optiques ultra-rapides à large bande à l'aide de l'apprentissage automatique(2020) |
| Source: |
ECOC2025, 51st European Conference on Optical Communication ; https://hal.science/hal-05325872 ; ECOC2025, 51st European Conference on Optical Communication, Sep 2025, Copenaghe, Denmark |
| Publisher Information: |
CCSD |
| Publication Year: |
2025 |
| Collection: |
Université de Franche-Comté (UFC): HAL |
| Subject Terms: |
Machine learning; Nonlinear fiber optics; [PHYS.PHYS.PHYS-OPTICS]Physics [physics]/Physics [physics]/Optics [physics.optics] |
| Subject Geographic: |
Copenaghe; Denmark |
| Description: |
International audience ; The importance of artificial intelligence (AI) in science was underscored by the decision to award the 2024 Nobel Prize in Physics to Hopfield and Hinton. Within the global field of AI, machine learning (ML) refers to algorithms and methods that learn patterns from data to make predictions or decisions without explicit programming, and within the field of guided wave photonics, ML has become an essential tool for understanding and exploiting the complex dynamics of nonlinear pulse propagation. This paper reviews our recent work in this field using ML to both control ultrafast nonlinear processes in fibre-based sources, and on a more fundamental level, to gain new physical insights into the underlying dynamics. In addition, we discuss the application of nonlinear fibre propagation as a computational resource. |
| Document Type: |
conference object |
| Language: |
English |
| Availability: |
https://hal.science/hal-05325872; https://hal.science/hal-05325872v1/document; https://hal.science/hal-05325872v1/file/Dudley-ECOC-2025%20%281%29.pdf |
| Rights: |
info:eu-repo/semantics/OpenAccess |
| Accession Number: |
edsbas.801DA23F |
| Database: |
BASE |