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Advancing PIC development using machine learning: from design to fabrication to optical characterization

From National Research Council Canada

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Linkhttps://ieeexplore.ieee.org/document/11046953
AuthorSearch for: 1ORCID identifier: https://orcid.org/0000-0002-0490-5224; Search for: 2ORCID identifier: https://orcid.org/0000-0003-3349-1590; Search for: 1; Search for: 3ORCID identifier: https://orcid.org/0000-0003-3525-2980; Search for: 1ORCID identifier: https://orcid.org/0000-0002-4851-3257; Search for: 1; Search for: 1; Search for: 1; Search for: 1ORCID identifier: https://orcid.org/0000-0003-4232-9130; Search for: 1ORCID identifier: https://orcid.org/0000-0003-3508-7428; Search for: ; Search for: ; Search for: ; Search for: ORCID identifier: https://orcid.org/0000-0001-9323-4452; Search for: ; Search for:
Affiliation
  1. National Research Council of Canada. Quantum and Nanotechnologies
  2. National Research Council of Canada. Digital Technologies
  3. National Research Council of Canada. Metrology Research Centre
FormatText, Article
Conference2025 Optical Fiber Communication Conference and Exhibition (OFC), March 30 - April 3, 2025, San Francisco, California, United States
Subjectlearning systems; machine learning; photonics
Abstract
This work leverages machine learning to accelerate PIC development in design, fabrication, and optical characterization, enabling efficient design exploration, precise fabrication corrections for structural fidelity, and high-resolution optical metrology to enhance process monitoring.
Publication date
PublisherOptica Publishing Group
IEEE
In
  • 2025 Optical Fiber Communication Conference and Exhibition (OFC), Th1F.1 (4 July 2025): 1–3.
Other version
  • Xu, Dan-Xia, Yuri Grinberg, Siegfried Janz, Sergey Dedyulin, Jianhao Zhang, Martin Vachon, Shurui Wang, et al. ‘Advancing PIC Development Using Machine Learning: From Design to Fabrication to Optical Characterization’. Optical Fiber Communication Conference (OFC) 2025, 2025, Th1F.1. https://doi.org/10.1364/ofc.2025.th1f.1.
LanguageEnglish
Peer reviewedYes
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Record identifier63da848f-7d4e-48ce-92f7-e38a73f0ea43
Record created2025-07-31
Record modified2025-08-01
Date modified: