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Security Analysis of Quantum Key Distribution with Small Block Length and Its Application to Quantum Space Communications

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Physical Review Letters 2021年第10期126卷 100501-100501页

作者： Charles Ci-Wen Lim Feihu Xu Jian-Wei Pan Artur Ekert Department of Electrical and Computer Engineering National University of Singapore 4 Engineering Drive 3 Singapore 117583 Centre for Quantum Technologies National University of Singapore 3 Science Drive 2 Singapore 117543 Hefei National Laboratory for Physical Sciences at Microscale and Department of Modern Physics University of Science and Technology of China Hefei 230026 China Shanghai Branch CAS Center for Excellence in Quantum Information and Quantum Physics University of Science and Technology of China Shanghai 201315 China Mathematical Institute University of Oxford Woodstock Rd Oxford OX2 6HD United Kingdom

The security of real-world quantum key distribution (QKD) critically depends on the number of data points the system can collect in a finite time interval. To date, state-of-the-art finite-key security analyses require block lengths in the order of 104 bits to obtain positive secret keys. This requirement, however, can be very difficult to achieve in practice, especially in the case of entanglement-based satellite QKD, where the overall channel loss can go up to 70 dB or more. Here, we provide an improved finite-key security analysis which reduces the block length requirement by 14% to 17% for standard channel and protocol settings. In practical terms, this reduction could save entanglement-based satellite QKD weeks of measurement time and resources, thereby bringing space-based QKD technology closer to reality. As an application, we use the improved analysis to show that the recently reported Micius QKD satellite is capable of generating positive secret keys with a 10−5 security level.

关键词： Quantum communication Quantum cryptography Quantum networks

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Antiferroelectric negative capacitance from a structural phase transition in zirconia

arXiv

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arXiv 2021年

作者： Hoffmann, Michael Wang, Zheng Tasneem, Nujhat Zubair, Ahmad Ravindran, Prasanna Venkat Tian, Mengkun Gaskell, Anthony Triyoso, Dina Consiglio, Steven Tapily, Kanda Clark, Robert Hur, Jae Pentapati, Sai Surya Kiran Dopita, Milan Yu, Shimeng Chern, Winston Kacher, Josh Reyes-Lillo, Sebastian E. Antoniadis, Dimitri Ravichandran, Jayakanth Slesazeck, Stefan Mikolajick, Thomas Khan, Asif Islam NaMLab GGmbH Dresden01187 Germany School of Electrical and Computer Engineering Georgia Institute of Technology AtlantaGA30332 United States Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02142 United States Institute for Electronics and Nanotechnology Georgia Institute of Technology AtlantaGA30332 United States TEL Technology Center America LLC 255 Fuller Rd. AlbanyNY12203 United States Department of Condensed Matter Physics Faculty of Mathematics and Physics Charles University Ke Karlovu 5 Prague12116 Czech Republic Izentis LLC PO Box 397002 CambridgeMA02139 United States School of Materials Science and Engineering Georgia Institute of Technology AtlantaGA30332 United States Departamento de Ciencias Físicas Universidad Andres Bello Santiago837-0136 Chile Department of Chemical Engineering and Materials Science University of Southern California Los AngelesCA90089 United States Institute of Semiconductors and Microsystems TU Dresden Dresden Germany Department of Electrical Engineering and Computer Sciences University of California BerkeleyCA94720 United States

Crystalline materials with broken inversion symmetry can exhibit a spontaneous electric polarization, which originates from a microscopic electric dipole moment. Long-range polar or anti-polar order of such permanent dipoles gives rise to ferroelectricity or antiferroelectricity, respectively. However, the recently discovered antiferroelectrics of fluorite structure (HfO2 and ZrO2) are different: A non-polar phase transforms into a polar phase by spontaneous inversion symmetry breaking upon the application of an electric field. Here, we show that this structural transition in antiferroelectric ZrO2gives rise to a negative capacitance, which is promising for overcoming the fundamental limits of energy efficiency in electronics. Our findings provide insight into the thermodynamically 'forbidden' region of the antiferroelectric transition in ZrO2and extend the concept of negative capacitance beyond ferroelectricity. This shows that negative capacitance is a more general phenomenon than previously thought and can be expected in a much broader range of materials exhibiting structural phase transitions. Copyright © 2021, The Authors. All rights reserved.

关键词： Electric fields

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基于深度学习技术的集群电动汽车及家庭热水系统灵活性预测

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engineering 2021年第8期7卷 141-169页

作者：胡俊杰周华嫣然周羿宏张海婧 Lars Nordstr?md 杨光亚 State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources (North China Electric Power University) Division of Electric Power and Energy Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Center for Electric Power and Energy Department of Electrical Engineering Technical University of Denmark

随着电网中间歇性可再生能源发电规模的增大，为了保证电能质量和频率的稳定性，电网对可控资源的需求也随之增加。需求响应（demand response, DR）资源的灵活性已成为解决这一问题的一个有价值的方法。然而，目前关于DR资源的灵活性... 详细信息

随着电网中间歇性可再生能源发电规模的增大，为了保证电能质量和频率的稳定性，电网对可控资源的需求也随之增加。需求响应（demand response, DR）资源的灵活性已成为解决这一问题的一个有价值的方法。然而，目前关于DR资源的灵活性预测问题尚未得到充分的研究。本研究应用一种深度学习技术，即结合时间卷积神经网络的TRANSFORMER模型（temporal convolution network-combined transformer）来预测电动汽车与家庭热水系统两种DR资源的聚合灵活性。所提出的灵活性预测方法使用了基于DR资源的历史用电数据以及为了辅助预测所提出的DR信号数据。所提方法不仅可以预测聚合灵活性的大小，还可以预测其维持时间。最后，本文通过算例仿真验证了灵活性预测结果的准确性。仿真结果表明，在不同的灵活性维持时间下，DR资源灵活性的大小会发生变化。文中所提出的DR资源灵活性预测方法展现了其在释放需求侧资源的灵活性以向电网提供备用容量方面的应用。

关键词：负荷灵活性电动汽车家庭热水系统结合时间卷积神经网络的Transformer模型深度学习

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Design optimization of BLDC motor using multi-objective plasma generation algorithm

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AIP Conference Proceedings 2024年第1期3217卷

作者： Sundaram B. Pandya Om S. Patel Ajay Kumar Kanak Kalita Pradeep Jangir Jasgurpreet Singh Chohan Sarita Rathee Laith Abualigah Electrical Engineering Department Shri K. J. Polytechnic Bholav Bharuch 392001 India Department Department of Mechanical Engineering JECRC University Jaipur 303905 India Department of Mechanical Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Avadi 600062 India Department of Biosciences Saveetha School of Engineering. Saveetha Institute of Medical and Technical Sciences Chennai 602105 India Department of Mechanical Engineering and University Centre for Research & Development Chandigarh University Mohali 140413 India Department of Electronics and Communication Engineering School of Engineering & Technology JECRC University Jaipur - 303 905 India Computer Science Department Al al-Bayt University Mafraq 25113 Jordan Department of Electrical and Computer Engineering Lebanese American University Byblos 13-5053 Lebanon Hourani Center for Applied Scientific Research Al-Ahliyya Amman University Amman 19328 Jordan MEU Research Unit Middle East University Amman 11831 Jordan

In this paper, a novel Multi-Objective Plasma Generation Optimization (MOPGO) algorithm is introduced. It integrates Non-Dominant Sorting (NDS) and Crowding Distance (CD) methods to solve multi- objective optimization problems effectively. The NDS approach preserves non-dominated solutions, while the CD method ensures diversity among solutions. MOPGO addresses key challenges in optimization such as Pareto dominance, solution diversity. This balanced approach achieves superior optimization performance by maintaining an equilibrium between global diversification and local intensification. The consequences for computational efficiency and solution quality are discussed and compared with other notable algorithms like Equilibrium Optimizer (EO), Thermal Exchange Optimization (TEO), Generalized Normal Distribution Optimization (GNDO) and Moth Flame Optimization (MFO).

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Tunable unidirectional nonlinear emission from transition-metal-dichalcogenide metasurfaces

arXiv

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arXiv 2021年

作者： Nauman, Mudassar Yan, Jingshi de Ceglia, Domenico Rahmani, Mohsen Kamali, Khosro Zangeneh de Angelis, Costantino Miroshnichenko, Andrey E. Lu, Yuerui Neshev, Dragomir N. Research School of Electrical Energy and Materials Engineering College of Engineering and Computer Science Australian National University CanberraACT2601 Australia ARC Centre of Excellence for Transformative Meta-Optical Systems Department of Electronic Materials Engineering Research School of Physics The Australian National University CanberraACT2601 Australia Department of Information Engineering University of Padova Via G. Gradenigo 6/B Padova Italy Advanced Optics and Photonics Laboratory Department of Engineering School of Science and Technology Nottingham Trent University NottinghamNG11 8NS United Kingdom Department of Information Engineering University of Brescia Via Branze 38 Brescia25123 Italy

Nonlinear light sources are central to a myriad of applications, driving a quest for their miniaturisation down to the nanoscale. In this quest, nonlinear metasurfaces hold a great promise, as they enhance nonlinear effects through their resonant photonic environment and high refractive index, such as in high-index dielectric metasurfaces. However, despite the sub-diffractive operation of dielectric metasurfaces at the fundamental wave, this condition is not fulfilled for the nonlinearly generated harmonic waves, thereby all nonlinear metasurfaces to date emit multiple diffractive beams. Here, we demonstrate the enhanced single-beam second- and third-harmonic generation in a metasurface of crystalline transition-metal-dichalcogenide material, offering the highest refractive index. We show that the interplay between the resonances of the metasurface allows for tuning of the unidirectional second-harmonic radiation in forward or backward direction, not possible in any bulk nonlinear crystal. Our results open new opportunities for metasurface-based nonlinear light-sources, including nonlinear mirrors and entangled-photon generation. Copyright © 2021, The Authors. All rights reserved.

关键词： Refractive index

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Predicting extreme events from data using deep machine learning: When and where

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Physical Review Research 2022年第2期4卷 023028-023028页

作者： Junjie Jiang Zi-Gang Huang Celso Grebogi Ying-Cheng Lai The Key Laboratory of Biomedical Information Engineering of Ministry of Education Institute of Health and Rehabilitation Science School of Life Science and Technology Research Center for Brain-inspired Intelligence Xi'an Jiaotong University The Key Laboratory of Neuro-informatics & Rehabilitation Engineering of Ministry of Civil Affairs Xi'an Shaanxi 710049 China School of Electrical Computer and Energy Engineering Arizona State University Tempe Arizona 85287 USA Institute for Complex Systems and Mathematical Biology School of Natural and Computing Sciences King's College University of Aberdeen Aberdeen AB24 3UE United Kingdom Department of Physics Arizona State University Tempe Arizona 85287 USA

We develop a framework based on the deep convolutional neural network (DCNN) for model-free prediction of the occurrence of extreme events both in time (“when”) and in space (“where”) in nonlinear physical systems of spatial dimension two. The measurements or data are a set of two-dimensional snapshots or images. For a desired time horizon of prediction, a proper labeling scheme can be designated to enable successful training of the DCNN and subsequent prediction of extreme events in time. Given that an extreme event has been predicted to occur within the time horizon, a space-based labeling scheme can be applied to predict, within certain resolution, the location at which the event will occur. We use synthetic data from the two-dimensional complex Ginzburg-Landau equation and empirical wind speed data from the North Atlantic Ocean to demonstrate and validate our machine-learning-based prediction framework. The trade-offs among the prediction horizon, spatial resolution, and accuracy are illustrated, and the detrimental effect of spatially biased occurrence of extreme events on prediction accuracy is discussed. The deep learning framework is viable for predicting extreme events in the real world.

关键词： Machine learning Spatiotemporal chaos Artificial neural networks Extreme event statistics

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Is perfect filtering enough leading to perfect phase correction for dMRI data?

arXiv

引用

arXiv 2021年

作者： Feihong, Liu Junwei, Yang Xiaowei, He Luping, Zhou Jun, Feng Dinggang, Shen School of Information Science and Technology Northwest University Xi’an China School of Biomedical Engineering ShanghaiTech University Shanghai China Department of Computer Science and Technology University of Cambridge Cambridge United Kingdom State-Province Joint Engineering Research Center of Advanced Networking and Intelligent Information Services School of Information Science and Technology Northwest University Xi’an China School of Electrical and Information Engineering University of Sydney Sydney Australia Shanghai United Imaging Intelligence Co. Ltd. Shanghai China

Being complex-valued and low in signal-to-noise ratios, magnitude based diffusion MRI is confounded by the noise-floor that falsely elevates signal magnitude and incurs bias to the commonly used diffusion indices, such as fractional anisotropy (FA). To avoid noise-floor, most existing phase correction methods explore improving filters to estimate the noise-free background phase. In this work, after diving into the phase correction procedures, we argue that even a perfect filter is insufficient for phase correction because the correction procedures are incapable of distinguishing sign-symbols of noise, resulting in artifacts (i.e., arbitrary signal loss). With this insight, we generalize the definition of noise-floor to a complex polar coordinate system and propose a calibration procedure that could conveniently distinguish noise sign-symbols. The calibration procedure is conceptually simple and easy to implement without relying on any external technique, while keeping distinctly effective. Extensive experimental results, including those on both synthetic and real diffusion MRI data, demonstrate that the calibrated procedures successfully mitigate artifacts in diffusion MR images and FA maps, with improved accuracy on estimating FA in particular. Copyright © 2021, The Authors. All rights reserved.

关键词： Magnetic resonance imaging

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Three-Dimensional Soundproof Acoustic Metacage

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Physical Review Letters 2021年第8期127卷 084301-084301页

作者： Chenkai Liu Jinjie Shi Wei Zhao Xiaoxi Zhou Chu Ma Ruwen Peng Mu Wang Zhi Hong Hang Xiaozhou Liu Johan Christensen Nicholas X. Fang Yun Lai MOE Key Laboratory of Modern Acoustics National Laboratory of Solid State Microstructures School of Physics and Collaborative Innovation Center of Advanced Microstructures Nanjing University Nanjing 210093 China School of Physical Science and Technology Soochow University Suzhou 215006 China School of Electronic and Information Engineering Soochow University Suzhou 215006 China Department of Electrical and Computer Engineering University of Wisconsin–Madison Madison Wisconsin 53706 USA Department of Mechanical Engineering Massachusetts Institute of Technology 77 Massachusetts Avenue Cambridge Massachusetts 02139 USA Institute for Advanced Study Soochow University Suzhou 215006 China Department of Physics Universidad Carlos III de Madrid ES-28916 Leganes Madrid Spain

In this Letter, we theoretically propose and experimentally demonstrate a three-dimensional soundproof acoustic cage structure, hereby denoted as an acoustic metacage. The metacage is composed of six acoustic metamaterial slabs with open holes and hidden bypass space coiling tunnels connected to the holes. Band structure analysis reveals a novel physical mechanism to open a low-frequency broad partial band gap via the band folding in other directions, which can also be interpreted by an effective medium with indefinite effective mass density and negative effective modulus. Transmission loss in simulations and in the acoustic impedance tube are administered. Strikingly, we prove that the soundproofing effect of the metacage is robust against the airflow perturbation induced by a fan. Our work paves a road for low-frequency airborne soundproof structures in the presence of ventilation.

关键词： Acoustic measurements Acoustic metamaterials Acoustic modeling Architectural acoustics Sound waves Acoustic techniques

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Parametric resonances in nonlinear plasmonics [Invited]

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Chinese Optics Letters 2019年第12期17卷 81-86页

作者： Shima Fardad Eric Schweisberger Alessandro Salandrino Department of Electrical Engineering and Computer Science The University of KansasLawrenceKS 66045USA Information and Telecommunication Technology Center The University of KansasLawrenceKS 66045USA

In the context of nonlinear plasmonics,we review the recently introduced concept of plasmonic parametric resonance(PPR)and discuss potential applications of such *** arises from the temporal modulation of one or more of the parameters governing the dynamics of a plasmonic system and can lead to the amplification of high-order sub-radiant plasmonic *** theory of PPR is reviewed,possible schemes of implementation are proposed,and applications in optical limiting are discussed.

关键词： nonlinear plasmon resonance

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Demonstration of two-dimensional extreme skin depth engineering in CMOS photonics foundry

Demonstration of two-dimensional extreme skin depth engineer...

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2020 Frontiers in Optics Conference, FiO 2020

作者： van Niekerk, Matthew Jahani, Saman Bickford, Justin Cho, Pak Anderson, Stephen Leake, Gerald Coleman, Daniel Fanto, Michael L. Tison, Christopher C. Howland, Gregory A. Jacob, Zubin Preble, Stefan F. Microsystems Engineering Rochester Institute of Technology RochesterNY14623 United States Birck Nanotechnology Center Purdue University West LafayetteIN47907 United States Department of Electrical Engineering California Institute of Technology PasadenaCA91125 United States U.S Army Research Laboratory AdelphiMD20783 United States Electrical Computer and Systems Engineering Department Rensselaer Polytechnic Institute TroyNY12180 United States State University New York Polytechnic Institute AlbanyNY12203 United States Air Force Research Laboratory RomeNY13441 United States School of Physics and Astronomy Rochester Institute of Technology RochesterNY14623 United States

We implement extreme skin depth engineering (e-skid) in two dimensions to suppress or enhance evanescent coupling on-demand. This is demonstrated experimentally with a large gap, bendless directional coupler exhibitin... 详细信息

ISBN: (纸本)9781943580804

关键词： CMOS integrated circuits

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