Machine-Learning Enabled Optimization for Robust Soliton Crystal Generation in Microring Resonators

C. Mazoukh*, L. Di Lauro*, B. Fischer, A. Aadhi, I. Alamgir, A. Eshaghi, B. E. Little, S. T. Chu, D. J. Moss, R. Morandotti

*Corresponding author for this work

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

Abstract

We illustrate a novel strategy to robustly generate soliton states in Hydex microring resonators pumped with a continuous-wave laser source, by employing genetic algorithms to optimize the parameters required for coherent state generation. © 2023 The Author(s). © Optica Publishing Group 2023.
Original languageEnglish
Title of host publicationCLEO 2023
PublisherOptica Publishing Group
ISBN (Print)9781957171258
DOIs
Publication statusPublished - May 2023
Event2023 Conference on Lasers and Electro-Optics (CLEO 2023) - San Jose, United States
Duration: 7 May 202312 May 2023
http://CLEOConference.org

Publication series

NameConference on Lasers and Electro-Optics, CLEO

Conference

Conference2023 Conference on Lasers and Electro-Optics (CLEO 2023)
Country/TerritoryUnited States
CitySan Jose
Period7/05/2312/05/23
Internet address

Bibliographical note

Full text of this publication does not contain sufficient affiliation information. With consent from the author(s) concerned, the Research Unit(s) information for this record is based on the existing academic department affiliation of the author(s).

Fingerprint

Dive into the research topics of 'Machine-Learning Enabled Optimization for Robust Soliton Crystal Generation in Microring Resonators'. Together they form a unique fingerprint.

Cite this