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We present a semianalytical method for designing meta-atoms in multilayered metasurfaces (MSs), relying on a rigorous model developed for multielement metagratings. Notably, this model properly accounts for near-field coupling effects,…

Applied Physics · Physics 2019-02-01 Shahar Levy , Yaniv Kerzhner , Ariel Epstein

The irreducible complexity of natural phenomena has led Graph Neural Networks to be employed as a standard model to perform representation learning tasks on graph-structured data. While their capacity to capture local and global patterns is…

Machine Learning · Computer Science 2024-02-13 Lorenzo Giusti

Polarization and wavelength multiplexing are the two most widely employed techniques to improve the capacity in the metasurfaces. Existing works have pushed each technique to its individual limits. For example, the polarization multiplexing…

Optics · Physics 2024-08-20 Yanjun Bao , Hongsheng Shi , Rui Wei , Boyou Wang , Zhou Zhou , Cheng-Wei Qiu , Baojun Li

The discovery of topological insulators has rapidly been followed by the advent of their photonic analogues, motivated by the prospect of backscattering-immune light propagation. So far, however, implementations have mainly relied on…

Optics · Physics 2019-08-16 Diaaaldin J. Bisharat , Daniel F. Sievenpiper

Metasurfaces have been rapidly advancing our command over the many degrees of freedom of light within compact, lightweight devices. However, so far, they have mostly been limited to manipulating light in free space. Grating couplers provide…

Geometric graph neural networks (GNNs) excel at capturing molecular geometry, yet their locality-biased message passing hampers the modeling of long-range interactions. Current solutions have fundamental limitations: extending cutoff radii…

Machine Learning · Computer Science 2025-09-29 Haodong Pan , Yusong Wang , Nanning Zheng , Caijui Jiang

Membrane-metasurfaces, formed by periodic arrangements of holes in a dielectric layer, are gaining attention for their easier manufacturing via subtractive techniques, unnecessity of substrates, and access to resonant near-fields. Despite…

Metamaterials bring sub-wavelength resonating structures together to overcome the limitations of conventional materials. The realization of active metadevices has been an outstanding challenge that requires electrically reconfigurable…

We present an exact treatment of layered many-body electronic systems in the presence of interlayer coupling within the Schwinger functional derivative approach on the Keldysh contour. Our transparent approach allows us to clarify the…

Strongly Correlated Electrons · Physics 2020-07-01 Christopher Lane

Mechanically reconfigurable metasurfaces capable of translation, rotation, and permutation have attracted considerable attention for high-capacity optical information storage and full-color holographic displays, owing to their low-power and…

Optics · Physics 2025-11-18 Ting Ma , Xianjin Liu , Qiwen Bao , Bolun Zhang , Jun-Jun Xiao

To this day, achieving broadband low-frequency sound absorption remains a challenge even with the possibilities promised by the advent of metamaterials and metasurfaces, especially when size and structural restrictions exist. Solving this…

The programmable artificial lattice, based on the controllability of coupling strengths and the scalability of multiple sites, is desperately desired in engineering metamaterials and exploring fundamental physics. In this work, we…

Applied Physics · Physics 2020-09-03 Shaochun Lin , Tian Tian , Pu Huang , Peiran Yin , Liang Zhang , Jiangfeng Du

Mutual Coupling (MC) is an unavoidable feature in Reconfigurable Intelligent Surfaces (RISs) with sub-wavelength inter-element spacing. Its inherent presence naturally leads to non-local RIS structures, which can be efficiently described…

Information Theory · Computer Science 2024-04-09 Dilki Wijekoon , Amine Mezghani , George C. Alexandropoulos , Ekram Hossain

Visual long-range interaction refers to modeling dependencies between distant feature points or blocks within an image, which can significantly enhance the model's robustness. Both CNN and Transformer can establish long-range interactions…

Computer Vision and Pattern Recognition · Computer Science 2023-03-13 Xiuxiu Bai , Shuaishuai Zhao , Yao Gao , Zhe Liu

Recently, graph neural networks have shown the superiority of modeling the complex topological structures in heterogeneous network-based recommender systems. Due to the diverse interactions among nodes and abundant semantics emerging from…

Machine Learning · Computer Science 2022-08-04 Tiankai Gu , Chaokun Wang , Cheng Wu , Jingcao Xu , Yunkai Lou , Changping Wang , Kai Xu , Can Ye , Yang Song

We present a computational framework for efficient optimization-based "inverse design" of large-area "metasurfaces" (subwavelength-patterned surfaces) for applications such as multi-wavelength and multi-angle optimizations, and…

While the celebrated graph neural networks yield effective representations for individual nodes of a graph, there has been relatively less success in extending to the task of graph similarity learning. Recent work on graph similarity…

Machine Learning · Computer Science 2021-08-20 Xiang Ling , Lingfei Wu , Saizhuo Wang , Tengfei Ma , Fangli Xu , Alex X. Liu , Chunming Wu , Shouling Ji

Metasurfaces composed of planar arrays of sub-wavelength artificial structures show promise for extraordinary light manipulation; they have yielded novel ultrathin optical components such as flat lenses, wave plates, holographic surfaces…

Subwavelength dielectric resonators assembled into metasurfaces have become a versatile tool for miniaturising optical components approaching the nanoscale. An important class of metasurface functionalities is associated with asymmetry in…

Graphene is a two-dimensional layer of carbon atoms arranged in a honeycomb lattice, whose outstanding properties makes it an excellent material for future electronic and photonic terahertz (THz) devices. In this work, we design hybrid…

Optics · Physics 2020-06-29 Tianjing Guo , Christos Argyropoulos
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