Towards intelligent fiber laser design by using a feed-forward neural network

Xinyang Liu, Regina Gumenyuk

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

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Abstract

We demonstrated a high accuracy prediction of the fiber laser output parameters by using a feed-forward neural network. We explored both the gain and spectral filter parameters to test the prediction performance of the neural network and realized the mapping between cavity parameters and laser output performance. We also investigated how the number of hidden layers could influence the accuracy of prediction. Based on the results, the output spectrum and temporal pulse profiles can be predicted with high accuracy in various fiber laser designs. Our work paves the way to intelligent laser design with ultimate autonomy.

Original languageEnglish
Title of host publicationAdvanced Lasers, High-Power Lasers, and Applications XIV
EditorsJun Liu, Shibin Jiang, Ingmar Hartl
PublisherSPIE
ISBN (Electronic)9781510667693
DOIs
Publication statusPublished - 2023
Publication typeA4 Article in conference proceedings
EventSPIE/COS Photonics Asia technical conferences - Beijing, China
Duration: 14 Oct 202316 Oct 2023

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume12760
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

ConferenceSPIE/COS Photonics Asia technical conferences
Country/TerritoryChina
CityBeijing
Period14/10/2316/10/23

Keywords

  • feed-forward neural network
  • Intelligent laser cavity design
  • laser output prediction

Publication forum classification

  • Publication forum level 0

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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