Deep Learning for Design and Retrieval of Plasmonic Nanostructures

Michael Mrejen; Itzik Malkiel; Achiya Nagler; Uri Arieli; Lior Wolf; Haim Suchowski

doi:10.23919/CLEO.2019.8749636

Deep Learning for Design and Retrieval of Plasmonic Nanostructures

Michael Mrejen, Itzik Malkiel, Achiya Nagler, Uri Arieli, Lior Wolf, Haim Suchowski

Tel Aviv University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

I We experimentally demonstrate a novel Deep Learning method capable of retrieving subwavelength dimensions from solely far-field measurements. Moreover, it also directly addresses the inverse problem i.e. obtaining a geometry for a desired electromagnetic response.

Original language	English
Title of host publication	2019 Conference on Lasers and Electro-Optics, CLEO 2019 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781943580576
DOIs	https://doi.org/10.23919/CLEO.2019.8749636
State	Published - May 2019
Event	2019 Conference on Lasers and Electro-Optics, CLEO 2019 - San Jose, United States Duration: 5 May 2019 → 10 May 2019

Publication series

Name	2019 Conference on Lasers and Electro-Optics, CLEO 2019 - Proceedings

Conference

Conference	2019 Conference on Lasers and Electro-Optics, CLEO 2019
Country/Territory	United States
City	San Jose
Period	5/05/19 → 10/05/19

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10.23919/CLEO.2019.8749636

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Mrejen, M., Malkiel, I., Nagler, A., Arieli, U., Wolf, L., & Suchowski, H. (2019). Deep Learning for Design and Retrieval of Plasmonic Nanostructures. In 2019 Conference on Lasers and Electro-Optics, CLEO 2019 - Proceedings Article 8749636 (2019 Conference on Lasers and Electro-Optics, CLEO 2019 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.23919/CLEO.2019.8749636

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title = "Deep Learning for Design and Retrieval of Plasmonic Nanostructures",

abstract = "I We experimentally demonstrate a novel Deep Learning method capable of retrieving subwavelength dimensions from solely far-field measurements. Moreover, it also directly addresses the inverse problem i.e. obtaining a geometry for a desired electromagnetic response.",

author = "Michael Mrejen and Itzik Malkiel and Achiya Nagler and Uri Arieli and Lior Wolf and Haim Suchowski",

note = "Publisher Copyright: {\textcopyright} 2019 The Author(s) 2019 OSA.; 2019 Conference on Lasers and Electro-Optics, CLEO 2019 ; Conference date: 05-05-2019 Through 10-05-2019",

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doi = "10.23919/CLEO.2019.8749636",

language = "אנגלית",

series = "2019 Conference on Lasers and Electro-Optics, CLEO 2019 - Proceedings",

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Mrejen, M, Malkiel, I, Nagler, A, Arieli, U, Wolf, L & Suchowski, H 2019, Deep Learning for Design and Retrieval of Plasmonic Nanostructures. in 2019 Conference on Lasers and Electro-Optics, CLEO 2019 - Proceedings., 8749636, 2019 Conference on Lasers and Electro-Optics, CLEO 2019 - Proceedings, Institute of Electrical and Electronics Engineers Inc., 2019 Conference on Lasers and Electro-Optics, CLEO 2019, San Jose, United States, 5/05/19. https://doi.org/10.23919/CLEO.2019.8749636

Deep Learning for Design and Retrieval of Plasmonic Nanostructures. / Mrejen, Michael; Malkiel, Itzik; Nagler, Achiya et al.
2019 Conference on Lasers and Electro-Optics, CLEO 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. 8749636 (2019 Conference on Lasers and Electro-Optics, CLEO 2019 - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Suchowski, Haim

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Mrejen M, Malkiel I, Nagler A, Arieli U, Wolf L , Suchowski H. Deep Learning for Design and Retrieval of Plasmonic Nanostructures. In 2019 Conference on Lasers and Electro-Optics, CLEO 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2019. 8749636. (2019 Conference on Lasers and Electro-Optics, CLEO 2019 - Proceedings). doi: 10.23919/CLEO.2019.8749636

Deep Learning for Design and Retrieval of Plasmonic Nanostructures

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