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Low-Velocity-Favored Transition Radiation

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Physical Review Letters 2023年第11期131卷 113002-113002页

作者： Jialin Chen Ruoxi Chen Fuyang Tay Zheng Gong Hao Hu Yi Yang Xinyan Zhang Chan Wang Ido Kaminer Hongsheng Chen Baile Zhang Xiao Lin Interdisciplinary Center for Quantum Information State Key Laboratory of Extreme Photonics and Instrumentation ZJU-Hangzhou Global Scientific and Technological Innovation Center College of Information Science & Electronic Engineering Zhejiang University Hangzhou 310027 China International Joint Innovation Center the Electromagnetics Academy at Zhejiang University Zhejiang University Haining 314400 China Department of Electrical and Computer Engineering Technion-Israel Institute of Technology Haifa 32000 Israel Department of Electrical and Computer Engineering Rice University Houston Texas 77005 USA Applied Physics Graduate Program Smalley-Curl Institute Rice University Houston Texas 77005 USA School of Electrical and Electronic Engineering Nanyang Technological University Singapore 639798 Singapore Department of Physics University of Hong Kong Hong Kong 999077 China Key Lab of Advanced Micro/Nano Electronic Devices & Smart Systems of Zhejiang Jinhua Institute of Zhejiang University Zhejiang University Jinhua 321099 China Shaoxing Institute of Zhejiang University Zhejiang University Shaoxing 312000 China Division of Physics and Applied Physics School of Physical and Mathematical Sciences Nanyang Technological University Singapore 637371 Singapore Centre for Disruptive Photonic Technologies Nanyang Technological University Singapore 637371 Singapore

When a charged particle penetrates through an optical interface, photon emissions emerge—a phenomenon known as transition radiation. Being paramount to fundamental physics, transition radiation has enabled many applications from high-energy particle identification to novel light sources. A rule of thumb in transition radiation is that the radiation intensity generally decreases with the decrease of particle velocity v; as a result, low-energy particles are not favored in practice. Here, we find that there exist situations where transition radiation from particles with extremely low velocities (e.g., v/c<10−3) exhibits comparable intensity as that from high-energy particles (e.g., v/c=0.999), where c is the light speed in free space. The comparable radiation intensity implies an extremely high photon extraction efficiency from low-energy particles, up to 8 orders of magnitude larger than that from high-energy particles. This exotic phenomenon of low-velocity-favored transition radiation originates from the interference of the excited Ferrell-Berreman modes in an ultrathin epsilon-near-zero slab. Our findings may provide a promising route toward the design of integrated light sources based on low-energy electrons and specialized detectors for beyond-standard-model particles.

关键词： Atom or molecule scattering from surfaces Atomic & molecular collisions Cherenkov radiation Crystal optics Electron beams & optics Light-matter interaction Optical sources & detectors Optical transient phenomena Plasmonics

Visualizing Field-free Deterministic Magnetic Switching of all–van der Waals Spin-Orbit Torque System Using Spin Ensembles in Hexagonal Boron Nitride

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arXiv 2025年

作者： Zhang, Xi Zhou, Jingcheng Hu, Chaowei Deng, Kuangyin Wang, Chuangtang Agarwal, Nishkarsh Jin, Hanshang Al-Matouq, Faris A. Xu, Stelo Trivedi, Roshan S. Li, Senlei Rathi, Sumedh Lu, Hanyi Jiang, Zhigang Taufour, Valentin Hovden, Robert Zhao, Liuyan Cheng, Ran Xu, Xiaodong Chu, Jiun-Haw Du, Chunhui Rita Wang, Hailong School of Physics Georgia Institute of Technology AtlantaGA30332 United States Department of Physics University of Washington SeattleWA98105 United States Department of Electrical and Computer Engineering University of California RiversideCA92521 United States Department of Physics University of Michigan Ann ArborMI48109 United States Department of Materials Science and Engineering University of Michigan Ann ArborMI48109 United States Department of Physics and Astronomy University of California DavisCA95616 United States Department of Physics University of California San Diego La Jolla CA92093 United States Applied Physics Program University of Michigan Ann ArborMI48109 United States Department of Physics and Astronomy University of California RiversideCA92521 United States Department of Materials Science and Engineering University of Washington SeattleWA98105 United States

Recently, optically active spin defects embedded in van der Waals (vdW) crystals have emerged as a transformative quantum sensing platform to explore cutting-edge materials science and quantum physics. Taking advantage of excellent solid-state integrability, this new class of spin defects can be arranged in controllable nanoscale proximity of target materials in vdW heterostructures, showing great promise for improving spatial resolution and field sensitivity of current sensing technologies. Building on this state-of-the-art measurement platform, here we report hexagonal boron nitride-based quantum imaging of field-free deterministic magnetic switching of room-temperature two-dimensional magnet Fe3GaTe2 in an all-vdW spin-orbit torque (SOT) system. By visualizing SOT-driven variations of nanoscale Fe3GaTe2 magnetic stray field profile under different conditions, we have revealed how the observed magnetic switching evolves from deterministic to indeterministic behavior due to the interplay between out-of-plane spins, in-plane spins and Joule heating. This understanding, which is otherwise difficult to access by conventional transport measurements, offers valuable insights on material design, testing, and evaluation of next-generation vdW spintronic devices. Copyright © 2025, The Authors. All rights reserved.

关键词： Van der Waals forces

UAS-Based Tools for Mapping and Monitoring Hydrothermal Systems: An Example from Mammoth Lakes, California

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UAS-Based Tools for Mapping and Monitoring Hydrothermal Syst...

2022 Geothermal Rising Conference: Using the Earth to Save the Earth, GRC 2022

作者： Zielinski, Laurie A. Glen, Jonathan M. Earney, Tait E. Rea-Downing, Grant H. Vaughan, R. Greg Kelly, Peter J. Keller, Gordon H. Dean, Branden J. Schermerhorn, William D. U.S. Geological Survey Geology Minerals Energy and Geophysics Science Center Moffett FieldCA United States University of Utah Department of Geology and Geophysics Salt Lake CityUT United States U.S. Geological Survey Astrogeology Science Center FlagstaffAZ United States U.S. Geological Survey Volcano Hazards Program VancouverWA United States University of California Santa Cruz Department of Electrical and Computer Engineering Santa CruzCA United States Mount Vernon WA United States

ISBN: (纸本)9781713871040

Unoccupied aerial systems (UAS) can accommodate a variety of tools for mapping and monitoring hydrothermal systems (e.g., magnetic, gas, photogrammetry, and thermal infrared [TIR]). These platforms offer increased speed, coverage area, and uniformity compared to ground-based measurements, as well as lower flight height - and therefore higher resolution - than occupied aircraft. We adapted a suite of tools for use with UAS and implemented these methods in a study focused on the area around Shady Rest Park, Mammoth Lakes, California, within the Long Valley Caldera. This location, which contains tree kills, gas vents, soil gas emissions, heated ground, and hydrothermal alteration, is the site of ongoing efforts to monitor changes in the surface expression of the local hydrothermal system. The methods applied in this study included: (1) airborne visible imagery for surficial mapping and the creation of high-resolution digital elevation models;(2) airborne magnetic measurements;(3) airborne TIR imagery;(4) airborne gas emission measurements;and (5) ground-based gravity measurements. We conducted these surveys in May and October of 2021, in part to establish baseline TIR and gas data against which future changes to the hydrothermal system may be assessed. UAS-based magnetic and ground-based gravity data were collected to map subsurface geology and to characterize potential subsurface controls on thermal anomalies and gas emissions. Results of these efforts at mapping and monitoring the hydrothermal system at Mammoth Lakes demonstrate how an integrated UAS- and ground-based approach may be applied more broadly to study other known or potential hydrothermal and volcanic systems. We consider the benefits and limitations of each method, particularly the TIR and gas sensors, which have less well-developed processing techniques in place for UAS applications. By integrating results from several of these different methods, however, the limitations facing each individual approach

关键词： Mapping

Meta-optic Accelerators for Object Classifiers

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arXiv 2022年

作者： Zheng, Hanyu Liu, Quan Zhou, You Kravchenko, Ivan I. Huo, Yuankai Valentine, Jason Department of Electrical and Computer Engineering Vanderbilt University NashvilleTN37212 United States Department of Computer Science Vanderbilt University NashvilleTN37212 United States Department of Mechanical Engineering Vanderbilt University NashvilleTN37212 United States Interdisciplinary Materials Science Program Vanderbilt University NashvilleTN37212 United States Center for Nanophase Materials Sciences Oak Ridge National Laboratory Oak RidgeTN37830 United States

Rapid advances in deep learning have led to paradigm shifts in a number of fields, from medical image analysis to autonomous systems. These advances, however, have resulted in digital neural networks with large computational requirements, resulting in high energy consumption and limitations in real-time decision making when computation resources are limited. Here, we demonstrate a meta-optic based neural network accelerator that can off-load computationally expensive convolution operations into high-speed and low-power optics. In this architecture, metasurfaces enable both spatial multiplexing and additional information channels, such as polarization, in object classification. End-to-end design is used to co-optimize the optical and digital systems resulting in a robust classifier that achieves 95% accurate classification of handwriting digits and 94% accuracy in classifying both the digit and its polarization state. This approach could enable compact, high-speed, and low-power image and information processing systems for a wide range of applications in machine-vision and artificial intelligence. Copyright © 2022, The Authors. All rights reserved.

关键词： Energy utilization

Z-Number Based Fuzzy Neural Network for System Identification

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SSRN

SSRN 2022年

作者： Abiyev, Rahib H. Kaynak, Okyay Aliev, Rafiq Near East University Department of Computer Engineering Mersin-10 North Cyprus Lefkosa Turkey Bogazici University Department of Electrical and Electronics Engineering Bebek Istanbul34342 Turkey Joint MBA Program Georgia State University United States Azerbaijan State Oil and Industry University 20 Azadliq ave. BakuAZ1010 Azerbaijan

In this paper, a novel Z-number based Fuzzy Neural Network (Z-FNN) is proposed for dynamic system identification. The architecture and learning algorithm of the proposed Z-FNN are designed. The inference mechanism of Z-FNN is based on distance measures and interpolative reasoning. The structure of the Z-FNN is accordingly designed using an interpolative reasoning scheme. Genetic Algorithms (GA) is applied to update the unknown parameters of the network. The proposed Z-FNN system is applied for dynamic plant identification. Its performance is compared with those obtained by the use of other approaches from the literature and it is proved that the proposed approach is a suitable alternative for practical applications that are characterized by uncertain and imprecise information. © 2022, The Authors. All rights reserved.

关键词： Fuzzy neural networks

Reduce Fingerprint Construction for Positioning IoT Devices Based on Generative Adversarial Nets 1

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Reduce Fingerprint Construction for Positioning IoT Devices ...

1st International Conference on Pervasive Artificial Intelligence, ICPAI 2020

作者： Tarekegn, Getaneh Berie Juang, Rong-Terng Lin, Hsin-Piao Munaye, Yirga Yayeh Belay Adege, Abebe National Taipei University of Technology Department of International Graduate Program in Electrical Engineering and Computer Science Taipei Taiwan Feng Chia University Department of Electronic Engineering Taichung Taiwan National Taipei University of Technology Department of Electronic Engineering Taipei Taiwan Debre Markos University Department of Information Technology Debre Markos Ethiopia

ISBN: (纸本)9781665404839

Fingerprint-based positioning is popular and applicable for Internet of Things (IoT) applications to offer seamless, intelligent and adaptive location-aware services for IoT devices. However, it takes time and cost to build the radio-map. This paper proposed deep convolutional Generative adversarial nets (DCGANs) to minimize the site survey time and cost, and to mitigate signal fluctuations. The radio-map was designed for receiving radio signals from detectable wireless local area network (WLAN) and cellular networks in scalable environments. The proposed fingerprinting-based positioning is a sequential combination of the hybrid support vector machine and long short-term memory algorithms. The experimental results indicate that the proposed method achieves a promising and reasonable positioning performance for IoT devices in scalable wireless environments. © 2020 IEEE.

关键词： Support vector machines

Negative photo conductivity triggered with visible light in wide bandgap oxide-based optoelectronic crossbar memristive array for photograph sensing and neuromorphic computing applications

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npj Unconventional Computing

npj Unconventional Computing 2024年第1期1卷 1-9页

作者： Dayanand Kumar Hanrui Li Manoj Kumar Rajbhar Abdul Momin Syed Nazek El-Atab Amit Singh Hoonkyung Lee Smart Advanced Memory Devices and Applications (SAMA) Laboratory Electrical and Computer Engineering Program Computer Electrical Mathematical Science and Engineering Division King Abdullah University of Science and Technology (KAUST) Thuwal Saudi Arabia Department of Physics and Astronomy University of Manchester Manchester UK Department of Physics Konkuk University Seoul Republic of Korea

Photoresponsivity studies of wide-bandgap oxide-based devices have emerged as a vibrant and popular research area. Researchers have explored various material systems in their quest to develop devices capable of responding to illumination. In this study, we engineered a mature wide-bandgap oxide-based bilayer heterostructure synaptic memristor to emulate the human brain for applications in neuromorphic computing and photograph sensing. The device exhibits advanced electric and electrophotonic synaptic functions, such as long-term potentiation (LTP), long-term depression (LTD), and paired-pulse facilitation (PPF), by applying successive electric and photonic pulses. Moreover, the device exhibits exceptional electrical SET and photonic RESET endurance, maintaining its stability for a minimum of 1200 cycles without any degradation. Density functional theory calculations of the band structures provide insights into the conduction mechanism of the device. Based on this memristor array, we developed an autoencoder and convolutional neural network for noise reduction and image recognition tasks, which achieves a peak signal-to-noise ratio of 562 and high accuracy of 84.23%, while consuming lower energy by four orders of magnitude compared with the Tesla P40 GPU. This groundbreaking research not only opens doors for the integration of our device into image processing but also represents a significant advancement in the realm of in-memory computing and photograph-sensing features in a single cell.

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Charge and Energy Transfer Dynamics of Hybridized Exciton-Polaritons in 2D Halide Perovskites

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arXiv 2023年

作者： Anantharaman, Surendra B. Lynch, Jason Stevens, Christopher E. Munley, Christopher Li, Chentao Hou, Jin Zhang, Hao Torma, Andrew Darlington, Thomas Coen, Francis Li, Kevin Majumdar, Arka Schuck, P. James Mohite, Aditya Harutyunyan, Hayk Hendrickson, Joshua R. Jariwala, Deep Department of Electrical and Systems Engineering University of Pennsylvania PhiladelphiaPA19104 United States KBR Inc. BeavercreekOH45431 United States Air Force Research Laboratory Sensors Directorate Wright-Patterson Air Force Base OH45433 United States Department of Physics University of Washington SeattleWA98195 United States Department of Physics Emory University AtlantaGA30322 United States Department of Chemical and Biomolecular Engineering Rice University HoustonTX77005 United States Department of Materials Science and Nanoengineering Rice University HoustonTX77005 United States Applied Physics Program Smalley‐Curl Institute Rice University HoustonTX77005 United States Department of Mechanical Engineering Columbia University New YorkNY10027 United States Department of Electrical and Computer Engineering University of Washington SeattleWA98195 United States

Excitons, bound electron-hole pairs, in Two-Dimensional Hybrid Organic Inorganic Perovskites (2D HOIPs) are capable of forming hybrid light-matter states known as exciton-polaritons (E-Ps) when the excitonic medium is confined in an optical cavity. In the case of 2D HOIPs, they can self-hybridize into E-Ps at specific thicknesses of the HOIP crystals that form a resonant optical cavity with the excitons. However, the fundamental properties of these self-hybridized E-Ps in 2D HOIPs, including their role in ultrafast energy and/or charge transfer at interfaces, remain unclear. Here, we demonstrate that > 0.5 µm thick 2D HOIP crystals on Au substrates are capable of supporting multiple-orders of self-hybridized E-P modes. These E-Ps have high Q factors (> 100) and modulate the optical dispersion for the crystal to enhance sub-gap absorption and emission. Through varying excitation energy and ultrafast measurements, we also confirm energy transfer from higher energy upper E-Ps to lower energy, lower E-Ps. Finally, we also demonstrate that E-Ps are capable of charge transport and transfer at interfaces. Our findings provide new insights into charge and energy transfer in E-Ps opening new opportunities towards their manipulation for polaritonic devices. © 2023, CC BY.

关键词： Charge transfer

Distributionally Robust Chance-Constrained Optimal Transmission Switching for Renewable Integration

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arXiv 2021年

作者： Zhou, Yuqi Zhu, Hao Hanasusanto, Grani A. The Department of Electrical & Computer Engineering The University of Texas at Austin AustinTX78712 United States The Graduate Program in Operations Research & Industrial Engineering The University of Texas at Austin AustinTX78712 United States

Increasing integration of renewable generation poses significant challenges to ensure robustness guarantees in real-time energy system decision-making. This work aims to develop a robust optimal transmission switching (OTS) framework that can effectively relieve grid congestion and mitigate renewable curtailment. We formulate a two-stage distributionally robust chance-constrained (DRCC) problem that assures limited constraint violations for any uncertainty distribution within an ambiguity set. Here, the second-stage recourse variables are represented as linear functions of uncertainty, yielding an equivalent reformulation involving linear constraints only. We utilize moment-based (mean-mean absolute deviation) and distance-based (∞-Wasserstein distance) ambiguity sets that lead to scalable mixed-integer linear program (MILP) formulations. Numerical experiments on the IEEE 14-bus and 118-bus systems have demonstrated the performance improvements of the proposed DRCC-OTS approaches in terms of guaranteed constraint violations and reduced renewable curtailment. In particular, the computational efficiency of the moment-based MILP approach, which is scenario-free with fixed problem dimensions, has been confirmed, making it suitable for real-time grid operations. Copyright © 2021, The Authors. All rights reserved.

关键词： Computational efficiency