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Mirrored Plasmonic Filter Design via Active Learning of Multi-Fidelity Physical Models

Song, Jialin and Tokpanov, Yury S. and Chen, Yuxin and Fleischman, Dagny and Fountaine, Katherine T. and Yue, Yisong and Atwater, Harry A. (2020) Mirrored Plasmonic Filter Design via Active Learning of Multi-Fidelity Physical Models. In: 2020 Conference on Lasers and Electro-Optics (CLEO). Optical Society of America , Washington, DC, Art. No. JTu2D.6. ISBN 9781943580767. https://resolver.caltech.edu/CaltechAUTHORS:20200923-131223809

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Abstract

We designed mirrored plasmonic filters using an advanced active machine learning algorithm that efficiently explores multiple physical models with different approximation fidelities and costs. This method is applicable to a variety of nanophotonics optimization problems.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
https://doi.org/10.1364/cleo_at.2020.jtu2d.6DOIArticle
https://ieeexplore.ieee.org/document/9192854PublisherArticle
ORCID:
AuthorORCID
Fountaine, Katherine T.0000-0002-0414-8227
Yue, Yisong0000-0001-9127-1989
Atwater, Harry A.0000-0001-9435-0201
Additional Information:© 2020 The Author(s).
Classification Code:OCIS codes: 220.4830, 130.7408
Record Number:CaltechAUTHORS:20200923-131223809
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20200923-131223809
Official Citation:J. Song, Y. S. Tokpanov, Y. Chen, D. Fleischman, K. T. Fountaine, Y. Yue, and H. A. Atwater, "Mirrored Plasmonic Filter Design via Active Learning of Multi-Fidelity Physical Models," in Conference on Lasers and Electro-Optics, OSA Technical Digest (Optical Society of America, 2020), paper JTu2D.6
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:105497
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:23 Sep 2020 20:21
Last Modified:23 Sep 2020 20:21

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