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Performing calculus with epsilon-near-zero metamaterials

Calculus is a fundamental subject in mathematics and extensively used in physics and astronomy. Performing calculus operations by analog computing has received much recent research interest because of its high speed and large data throughput; however, current analog calculus frameworks suffer from b...

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Autores principales: Li, Hao, Fu, Pengyu, Zhou, Ziheng, Sun, Wangyu, Li, Yue, Wu, Jiamin, Dai, Qionghai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Association for the Advancement of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9328691/
https://www.ncbi.nlm.nih.gov/pubmed/35895825
http://dx.doi.org/10.1126/sciadv.abq6198
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author Li, Hao
Fu, Pengyu
Zhou, Ziheng
Sun, Wangyu
Li, Yue
Wu, Jiamin
Dai, Qionghai
author_facet Li, Hao
Fu, Pengyu
Zhou, Ziheng
Sun, Wangyu
Li, Yue
Wu, Jiamin
Dai, Qionghai
author_sort Li, Hao
collection PubMed
description Calculus is a fundamental subject in mathematics and extensively used in physics and astronomy. Performing calculus operations by analog computing has received much recent research interest because of its high speed and large data throughput; however, current analog calculus frameworks suffer from bulky sizes and relatively low integration densities. In this work, we introduce the concept of an epsilon-near-zero (ENZ) metamaterial processing unit (MPU) that performs differentiation and integration on analog signals to achieve extreme miniaturization at the subwavelength scale by generating desired dispersions of the ENZ metamaterials with photonic doping. To show the feasibility of this proposal, we further build an experimental analog image edge extraction system with a differentiating ENZ-MPU as its compute core. With a computing density theoretically analyzed to be several tera-operations per second and square micrometer, the proposed ENZ-MPU is scalable and configurable for more complex computations, providing an effective solution for analog calculus operators with extreme computing density and data throughput.
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spelling pubmed-93286912022-08-09 Performing calculus with epsilon-near-zero metamaterials Li, Hao Fu, Pengyu Zhou, Ziheng Sun, Wangyu Li, Yue Wu, Jiamin Dai, Qionghai Sci Adv Physical and Materials Sciences Calculus is a fundamental subject in mathematics and extensively used in physics and astronomy. Performing calculus operations by analog computing has received much recent research interest because of its high speed and large data throughput; however, current analog calculus frameworks suffer from bulky sizes and relatively low integration densities. In this work, we introduce the concept of an epsilon-near-zero (ENZ) metamaterial processing unit (MPU) that performs differentiation and integration on analog signals to achieve extreme miniaturization at the subwavelength scale by generating desired dispersions of the ENZ metamaterials with photonic doping. To show the feasibility of this proposal, we further build an experimental analog image edge extraction system with a differentiating ENZ-MPU as its compute core. With a computing density theoretically analyzed to be several tera-operations per second and square micrometer, the proposed ENZ-MPU is scalable and configurable for more complex computations, providing an effective solution for analog calculus operators with extreme computing density and data throughput. American Association for the Advancement of Science 2022-07-27 /pmc/articles/PMC9328691/ /pubmed/35895825 http://dx.doi.org/10.1126/sciadv.abq6198 Text en Copyright © 2022 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC). https://creativecommons.org/licenses/by-nc/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license (https://creativecommons.org/licenses/by-nc/4.0/) , which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited.
spellingShingle Physical and Materials Sciences
Li, Hao
Fu, Pengyu
Zhou, Ziheng
Sun, Wangyu
Li, Yue
Wu, Jiamin
Dai, Qionghai
Performing calculus with epsilon-near-zero metamaterials
title Performing calculus with epsilon-near-zero metamaterials
title_full Performing calculus with epsilon-near-zero metamaterials
title_fullStr Performing calculus with epsilon-near-zero metamaterials
title_full_unstemmed Performing calculus with epsilon-near-zero metamaterials
title_short Performing calculus with epsilon-near-zero metamaterials
title_sort performing calculus with epsilon-near-zero metamaterials
topic Physical and Materials Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9328691/
https://www.ncbi.nlm.nih.gov/pubmed/35895825
http://dx.doi.org/10.1126/sciadv.abq6198
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