Plasmonic and Dielectric Nanostructures: Distinguishing Size, Material, and Dielectric Environment via Machine Learning

Aniket Pant; Kannatassen Appavoo

doi:10.1364/CLEO_SI.2021.SM1Q.6

Conference on Lasers and Electro-Optics
OSA Technical Digest (Optica Publishing Group, 2021),
paper SM1Q.6
•https://doi.org/10.1364/CLEO_SI.2021.SM1Q.6

Plasmonic and Dielectric Nanostructures: Distinguishing Size, Material, and Dielectric Environment via Machine Learning

Aniket Pant and Kannatassen Appavoo

CLEO: Science and Innovations 2021

San Jose, California United States
9–14 May 2021
ISBN: 978-1-943580-91-0

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Quantum Photonics and Machine Learning (SM1Q)

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A. Pant and K. Appavoo, "Plasmonic and Dielectric Nanostructures: Distinguishing Size, Material, and Dielectric Environment via Machine Learning," in Conference on Lasers and Electro-Optics, J. Kang, S. Tomasulo, I. Ilev, D. Müller, N. Litchinitser, S. Polyakov, V. Podolskiy, J. Nunn, C. Dorrer, T. Fortier, Q. Gan, and C. Saraceno, eds., OSA Technical Digest (Optica Publishing Group, 2021), paper SM1Q.6.

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Abstract

We employ machine learning, coupled with linear and nonlinear dimensionality reduction strategies, to distinguish between plasmonic and dielectric optical response of nanostructures and to understand the role of structural parameters and local environment.

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