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Software-defined metasurfaces are electromagnetically ultra-thin, artificial components that can provide engineered and externally controllable functionalities. The control over these functionalities is enabled by the metasurface…

Metasurfaces have provided a novel and promising platform for the realization of compact and large-scale optical devices. The conventional metasurface design approach assumes periodic boundary conditions for each element, which is…

Dynamic metasurface antennas (DMAs), surfaces patterned with reconfigurable metamaterial elements (meta-atoms) that couple waves from waveguides or cavities to free space, are a promising technology to realize 6G wireless base stations and…

Signal Processing · Electrical Eng. & Systems 2024-12-03 Hugo Prod'homme , Philipp del Hougne

Tunable metasurfaces are ultra-thin, artificial electromagnetic components that provide engineered and externally adjustable functionalities. The programmable metasurface, the HyperSurFace, concept consists in integrating controllers within…

One of the most promising metasurface architectures for the microwave and terahertz frequency ranges consists of three patterned metallic layers separated by dielectrics. Such metasurfaces are well suited to planar fabrication techniques…

Optics · Physics 2021-04-08 Andreas E. Olk , David A. Powell

Metamaterials are composed of periodic subwavelength metal/dielectric structures that resonantly couple to the electric and/or magnetic components of the incident electromagnetic fields, exhibiting properties that are not found in nature.…

Optics · Physics 2016-11-29 Hou-Tong Chen , Antoinette J Taylor , Nanfang Yu

Optical multiplexing is a key technique that enhances the capacity of optical systems by independently modulating various optical parameters to carry distinct information. Among these parameters, wavelength, polarization, and angle are the…

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

We are interested to explore the limit in using deep learning (DL) to study the electromagnetic response for complex and random metasurfaces, without any specific applications in mind. For simplicity, we focus on a simple pure reflection…

Signal Processing · Electrical Eng. & Systems 2024-06-19 Tianning Zhang , Chun Yun Kee , Yee Sin Ang , L. K. Ang

Metasurfaces represent one of the most vibrant fields of modern science and technology. A metasurface is a complex electromagnetic structure, that is typically deeply subwavelength in thickness, electrically large in transverse size and…

Optics · Physics 2017-11-01 Yousef Vahabzadeh , Nima Chamanara , Karim Achouri , Christophe Caloz

Metasurfaces based on gap surface-plasmon resonators allow one to arbitrarily control the phase, amplitude and polarization of reflected light with high efficiency. However, the performance of densely-packed metasurfaces is reduced, often…

Replacing electrons with photons is a compelling route towards light-speed, highly parallel, and low-power artificial intelligence computing. Recently, all-optical diffractive neural deep neural networks have been demonstrated. However, the…

Signal Processing · Electrical Eng. & Systems 2021-07-19 Xuhao Luo , Yueqiang Hu , Xin Li , Xiangnian Ou , Jiajie Lai , Na Liu , Huigao Duan

Metasurfaces have enabled precise electromagnetic wave manipulation with strong potential to obtain unprecedented functionalities and multifunctional behavior in flat optical devices. These advantages in precision and functionality come at…

Two-dimensional (2D) graphene-like layered semiconductors provide a new platform for materials research because of their unique mechanical, electronic and optical attributes. Their in-plane covalent bonding and dangling-bond-free surface…

Materials Science · Physics 2018-08-29 Zhiming Shi , Xinjiang Wang , Yuanhui Sun , Yawen Li , Lijun Zhang

Metasurfaces have emerged as transformative electromagnetic structures for wireless communications, enabling the real-time control over wave propagation, yielding potential for improved data rates, privacy, energy efficiency and even…

Conventional acoustic metasurfaces are constructed with gradiently ``local'' phase shift profiles provided by subunits. The local strategy implies the ignorance of the mutual coupling between subunits, which limits the efficiency of…

Applied Physics · Physics 2021-08-04 Hua Ding , Xinsheng Fang , Bin Jia , Nengyin Wang , Qian Cheng , Yong Li

All-dielectric metasurfaces exhibit exotic electromagnetic responses, similar to those obtained with metal-based metamaterials. Research in all-dielectric metasurfaces currently uses relatively simple unit-cell designs, but increased…

Optics · Physics 2020-12-10 Yang Deng , Simiao Ren , Kebin Fan , Jordan M. Malof , Willie J. Padilla

Compared to the conventional metasurface design, machine learning-based methods have recently created an inspiring platform for an inverse realization of the metasurfaces. Here, we have used the Deep Neural Network (DNN) for the generation…

Machine Learning · Computer Science 2021-11-10 Fardin Ghorbani , Javad Shabanpour , Sina Beyraghi , Hossein Soleimani , Homayoon Oraizi , Mohammad Soleimani

Metasurfaces are promising two-dimensional metamaterials that are engineered to provide unique properties or functionalities absent in naturally occurring homogeneous surfaces. Here, we report a type of metasurface for tailored…

Optics · Physics 2014-05-21 Jiao Lin , Qian Wang , Guanghui Yuan , Luping Du , Shan Shan Kou , Xiao-Cong Yuan

Typical acoustic refractive metasurfaces governed by generalized Snell law require several types of subwavelength subunits to provide an extra phase gradient along the surface. This design strategy, however, has several kinds of drawback.…

Applied Physics · Physics 2019-09-18 Zhilin Hou , Xinsheng Fang , Yong Li , Badreddine Assouar

The goal of this work is to address two limitations in autoencoder-based models: latent space interpretability and compatibility with unstructured meshes. This is accomplished here with the development of a novel graph neural network (GNN)…

Machine Learning · Computer Science 2023-02-20 Shivam Barwey , Varun Shankar , Venkatasubramanian Viswanathan , Romit Maulik
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