Breaking the fabrication determined resolution limit of photonic crystal wavemeter by machine learning

Jocelyn Hofs, Takumasa Kodama, Shengji Jin, Takasumi Tanabe

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

By utilizing random localization patterns as training data for machine learning, we achieved a 0.2-nm wavelength resolution with a fabricated photonic crystal wavemeter, which greatly exceeds the limit imposed by the fabrication.

Original languageEnglish
Title of host publicationCLEO
Subtitle of host publicationScience and Innovations, CLEO_SI 2020
PublisherOptica Publishing Group (formerly OSA)
ISBN (Print)9781943580767
DOIs
Publication statusPublished - 2020
EventCLEO: Science and Innovations, CLEO_SI 2020 - Washington, United States
Duration: 2020 May 102020 May 15

Publication series

NameOptics InfoBase Conference Papers
VolumePart F183-CLEO-SI 2020
ISSN (Electronic)2162-2701

Conference

ConferenceCLEO: Science and Innovations, CLEO_SI 2020
Country/TerritoryUnited States
CityWashington
Period20/5/1020/5/15

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Mechanics of Materials

Fingerprint

Dive into the research topics of 'Breaking the fabrication determined resolution limit of photonic crystal wavemeter by machine learning'. Together they form a unique fingerprint.

Cite this