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Metasurface for artificial neural computing (Conference Presentation)
Author(s): Zongfu Yu

Paper Abstract

We show that optical waves passing through a nanophotonic medium can perform artificial neural computing. Complex information, such as an image, is encoded in the wave front of input light. The medium continuously transforms the wave front to realize highly sophisticated computing tasks such as image recognition. At the output, optical energy is concentrated to well defined locations, which for example can be interpreted as the identity of the object in the image. These computing media can be as small as tens of wavelengths in size and thus offer extremely high computing density. They exploit sub-wavelength linear and nonlinear scatterers to realize sophisticated input-output mapping far beyond traditional nanophotonic devices. To enable these complex neural computing, we draw inspiration from artificial neural network and use stochastic gradient decent to optimize nonlinear nanophotonic structures with structural gradient computed from adjoint state method.

Paper Details

Date Published: 9 September 2019
Proc. SPIE 11080, Metamaterials, Metadevices, and Metasystems 2019, 110802E (9 September 2019); doi: 10.1117/12.2528792
Show Author Affiliations
Zongfu Yu, Univ. of Wisconsin-Madison (United States)

Published in SPIE Proceedings Vol. 11080:
Metamaterials, Metadevices, and Metasystems 2019
Nader Engheta; Mikhail A. Noginov; Nikolay I. Zheludev, Editor(s)

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