Machine Learning Design of Plasmonic Apertures for Optical Nanotweezers

Neuton Li; Vivek Raj Shrestha; Jasper Cadusch; Zhe Xu; Kenneth B. Crozier; Kenneth B. Crozier

doi:10.1364/LS.2019.LTh3E.4

Frontiers in Optics + Laser Science APS/DLS
OSA Technical Digest (Optica Publishing Group, 2019),
paper LTh3E.4
•https://doi.org/10.1364/LS.2019.LTh3E.4

Machine Learning Design of Plasmonic Apertures for Optical Nanotweezers

Neuton Li, Vivek Raj Shrestha, Jasper Cadusch, Zhe Xu, and Kenneth B. Crozier

Laser Science 2019

Washington, DC United States
15–19 September 2019
ISBN: 978-1-943580-67-5

From the session
Nobel Prize Symposium II (LTh3E)

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N. Li, V. R. Shrestha, J. Cadusch, Z. Xu, and K. B. Crozier, "Machine Learning Design of Plasmonic Apertures for Optical Nanotweezers," in Frontiers in Optics + Laser Science APS/DLS, OSA Technical Digest (Optica Publishing Group, 2019), paper LTh3E.4.

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Abstract

We present a new approach to design plasmonic structures for optical trapping. Using a simulated annealing algorithm, the shape of a nanoaperture is optimized. An order of magnitude increase in trapping potential is predicted.

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