Dataset Information

Magnetic Hyperbolic Metasurface: Concept, Design, and Applications.

ABSTRACT: A fundamental cornerstone in nanophotonics is the ability to achieve hyperbolic dispersion of surface plasmons, which shows excellent potentials in many unique applications, such as near-field heat transport, planar hyperlens, strongly enhanced spontaneous emission, and so forth. The hyperbolic metasurfaces with such an ability, however, are currently restricted to electric hyperbolic metasurface paradigm, and realization of magnetic hyperbolic metasurfaces remains elusive despite the importance of manipulating magnetic surface plasmons (MSPs) at subwavelength scale. Here, magnetic hyperbolic metasurfaces are proposed and designed, on which diffraction-free propagation, anomalous diffraction, negative refraction, and frequency-dependent strong spatial distributions of the MSPs in the hyperbolic regime are experimentally observed at microwave frequencies. The findings can be applied to manipulate MSPs and design planarized devices for near-field focusing, imaging, and spatial multiplexers. This concept is also generalizable to terahertz and optical frequencies and inspires novel quantum optical apparatuses with strong magnetic light-matter interactions.

SUBMITTER: Yang Y

PROVIDER: S-EPMC6299717 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature

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Magnetic Hyperbolic Metasurface: Concept, Design, and Applications.

Yang Yihao Y Qin Pengfei P Zheng Bin B Shen Lian L Wang Huaping H Wang Zuojia Z Li Erping E Singh Ranjan R Chen Hongsheng H

Advanced science (Weinheim, Baden-Wurttemberg, Germany) 20181112 12

A fundamental cornerstone in nanophotonics is the ability to achieve hyperbolic dispersion of surface plasmons, which shows excellent potentials in many unique applications, such as near-field heat transport, planar hyperlens, strongly enhanced spontaneous emission, and so forth. The hyperbolic metasurfaces with such an ability, however, are currently restricted to electric hyperbolic metasurface paradigm, and realization of magnetic hyperbolic metasurfaces remains elusive despite the importance ...[more]

PMID: 30581718

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Project description:Hyperbolic neural networks have been popular in the recent past due to their ability to represent hierarchical data sets effectively and efficiently. The challenge in developing these networks lies in the nonlinearity of the embedding space namely, the Hyperbolic space. Hyperbolic space is a homogeneous Riemannian manifold of the Lorentz group which is a semi-Riemannian manifold, i.e. a manifold equipped with an indefinite metric. Most existing methods (with some exceptions) use local linearization to define a variety of operations paralleling those used in traditional deep neural networks in Euclidean spaces. In this paper, we present a novel fully hyperbolic neural network which uses the concept of projections (embeddings) followed by an intrinsic aggregation and a nonlinearity all within the hyperbolic space. The novelty here lies in the projection which is designed to project data on to a lower-dimensional embedded hyperbolic space and hence leads to a nested hyperbolic space representation independently useful for dimensionality reduction. The main theoretical contribution is that the proposed embedding is proved to be isometric and equivariant under the Lorentz transformations, which are the natural isometric transformations in hyperbolic spaces. This projection is computationally efficient since it can be expressed by simple linear operations, and, due to the aforementioned equivariance property, it allows for weight sharing. The nested hyperbolic space representation is the core component of our network and therefore, we first compare this representation - independent of the network - with other dimensionality reduction methods such as tangent PCA, principal geodesic analysis (PGA) and HoroPCA. Based on this equivariant embedding, we develop a novel fully hyperbolic graph convolutional neural network architecture to learn the parameters of the projection. Finally, we present experiments demonstrating comparative performance of our network on several publicly available data sets.

Dataset Information

Magnetic Hyperbolic Metasurface: Concept, Design, and Applications.

Publications

Magnetic Hyperbolic Metasurface: Concept, Design, and Applications.

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