ArticleScience advances2022
Performing calculus with epsilon-near-zero metamaterials.
Article in Science advances, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Ohm's law of electromagnetic ideal fluids: impedance-governed supercoupling in complex near-zero-index networks.Nature communications · 2026Article
- Computational magnetic metasurfaces in the low radiofrequency regime.Scientific reports · 2025Article
- Silver Nanowires Epsilon-Negative Metacomposites in Constructing Laminated Structure Meta-Capacitors.Small (Weinheim an der Bergstrasse, Germany) · 2025Article
- Femtojoule optical nonlinearity for deep learning with incoherent illumination.Science advances · 2025Article
- Reconfigurable metamaterial processing units that solve arbitrary linear calculus equations.Nature communications · 2024Article
- Direct electromagnetic information processing with planar diffractive neural network.Science advances · 2024Article
- Negative capacitors and inductors enabling wideband waveguide metatronics.Nature communications · 2023Article
- Controlling coherent perfect absorption via long-range connectivity of defects in three-dimensional zero-index media.Nanophotonics (Berlin, Germany) · 2023Article
- Transmission-type photonic doping for high-efficiency epsilon-near-zero supercoupling.Nature communications · 2023Article
- Addressing the Impact of Surface Roughness on Epsilon-Near-Zero Silicon Carbide Substrates.ACS photonics · 2023Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.