Open Access
21 December 2022 Computation at the speed of light: metamaterials for all-optical calculations and neural networks
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Abstract

The explosion in the amount of information that is being processed is prompting the need for new computing systems beyond existing electronic computers. Photonic computing is emerging as an attractive alternative due to performing calculations at the speed of light, the change for massive parallelism, and also extremely low energy consumption. We review the physical implementation of basic optical calculations, such as differentiation and integration, using metamaterials, and introduce the realization of all-optical artificial neural networks. We start with concise introductions of the mathematical principles behind such optical computation methods and present the advantages, current problems that need to be overcome, and the potential future directions in the field. We expect that our review will be useful for both novice and experienced researchers in the field of all-optical computing platforms using metamaterials.

CC BY: © The Authors. Published by SPIE and CLP under a Creative Commons Attribution 4.0 International License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.
Trevon Badloe, Seokho Lee, and Junsuk Rho "Computation at the speed of light: metamaterials for all-optical calculations and neural networks," Advanced Photonics 4(6), 064002 (21 December 2022). https://doi.org/10.1117/1.AP.4.6.064002
Received: 18 October 2022; Accepted: 29 November 2022; Published: 21 December 2022
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CITATIONS
Cited by 28 scholarly publications.
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KEYWORDS
Artificial neural networks

Photonic metamaterials

Optical metamaterials

Design and modelling

Edge detection

Reflection

Computing systems

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