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Self-Propelled Detachment upon Coalescence of Surface Bubbles

Physical Review Letters 2021年第23期127卷 235501-235501页

作者： Pengyu Lv Pablo Peñas Hai Le The Jan Eijkel Albert van den Berg Xuehua Zhang Detlef Lohse State Key Laboratory for Turbulence and Complex Systems Department of Mechanics and Engineering Science Beijing Innovation Center for Engineering Science and Advanced Technology College of Engineering Peking University Beijing 100871 People’s Republic of China Physics of Fluids group Faculty of Science and Technology Max Planck—University of Twente Center for Complex Fluid Dynamics MESA+Institute and J. M. Burgers Centre for Fluid Dynamics University of Twente P.O. Box 217 7500 AE Enschede Netherlands BIOS Lab-on-a-Chip group Faculty of Electrical Engineering Max Planck—University of Twente Center for Complex Fluid Dynamics Mathematics and Computer Science MESA+Institute University of Twente P.O. Box 217 7500 AE Enschede Netherlands Department of Chemical & Materials Engineering University of Alberta Edmonton Alberta T6G1H9 Canada Max Planck Institute for Dynamics and Self-Organization 37077 Göttingen Germany

The removal of microbubbles from substrates is crucial for the efficiency of many catalytic and electrochemical gas evolution reactions in liquids. The current work investigates the coalescence and detachment of bubbles generated from catalytic decomposition of hydrogen peroxide. Self-propelled detachment, induced by the coalescence of two bubbles, is observed at sizes much smaller than those determined by buoyancy. Upon coalescence, the released surface energy is partly dissipated by the bubble oscillations, working against viscous drag. The remaining energy is converted to the kinetic energy of the out-of-plane jumping motion of the merged bubble. The critical ratio of the parent bubble sizes for the jumping to occur is theoretically derived from an energy balance argument and found to be in agreement with the experimental results. The present results provide both physical insight for the bubble interactions and practical strategies for applications in chemical engineering and renewable energy technologies like electrolysis.

关键词： Drops & bubbles

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Adversarial deep learning in EEG biometrics

arXiv

引用

arXiv 2019年

作者： Özdenizci, Ozan Wang, Ye Koike-Akino, Toshiaki Erdoğmuş, Deniz Cognitive Systems Laboratory Department of Electrical and Computer Engineering Northeastern University BostonMA United States Mitsubishi Electric Research Laboratories CambridgeMA United States

Deep learning methods for person identification based on electroencephalographic (EEG) brain activity encounters the problem of exploiting the temporally correlated structures or recording session specific variability within EEG. Furthermore, recent methods have mostly trained and evaluated based on single session EEG data. We address this problem from an invariant representation learning perspective. We propose an adversarial inference approach to extend such deep learning models to learn session-invariant person-discriminative representations that can provide robustness in terms of longitudinal usability. Using adversarial learning within a deep convolutional network, we empirically assess and show improvements with our approach based on longitudinally collected EEG data for person identification from half-second EEG epochs. Copyright © 2019, The Authors. All rights reserved.

关键词： Biometrics

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Roadmap on Atomic-scale Semiconductor Devices

arXiv

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arXiv 2025年

作者： Schofield, Steven R. Fisher, Andrew J. Ginossar, Eran Lyding, Joseph W. Silver, Richard Fei, Fan Namboodiri, Pradeep Wyrick, Jonathan Masteghin, M.G. Cox, D.C. Murdin, B.N. Clowes, S.K. Keizer, Joris G. Simmons, Michelle Y. Stemp, Holly G. Morello, Andrea Voisin, Benoit Rogge, Sven Wolkow, Robert A. Livadaru, Lucian Pitters, Jason Stock, Taylor J.Z. Curson, Neil J. Butera, Robert E. Pavlova, Tatiana V. Jakob, A.M. Spemann, D. Räcke, P. Schmidt-Kaler, F. Jamieson, D.N. Pratiush, Utkarsh Duscher, Gerd Kalinin, Sergei V. Kazazis, Dimitrios Constantinou, Procopios Aeppli, Gabriel Ekinci, Yasin Owen, James H.G. Fowler, Emma Moheimani, S.O. Reza Randall, John N. Misra, Shashank Ivie, Jeffrey Allemang, Christopher R. Anderson, Evan M. Bussmann, Ezra Campbell, Quinn Gao, Xujiao Lu, Tzu-Ming Schmucker, Scott W. London Centre for Nanotechnology University College London 17-19 Gordon St WC1H 0AH United Kingdom Department of Physics and Astronomy University College London WC1E 6BT United Kingdom School of Mathematics and Physics University of Surrey United Kingdom Department of Electrical and Computer Engineering University of Illinois UrbanaIL61801 United States Atom Scale Device Group National Institute of Standards and Technology GaithersburgMD20899 United States Advanced Technology Institute University of Surrey GU2 7XH United Kingdom School of Physics University of New South Wales Sydney Australia School of Electrical Engineering & Telecommunications UNSW Sydney Australia Silicon Quantum Computing Pty Ltd Sydney Australia Australia University of Alberta Department of Physics EdmontonT6G 2E1 Canada National Research Council of Canada Quantum and Nanotechnologies Research Centre 11421 Saskatchewan Drive NW EdmontonT6G 2M9 Canada Department of Electronic and Electrical Engineering University College London WC1E 7JE United Kingdom Laboratory for Physical Sciences University of Maryland College ParkMD20740 United States Prokhorov General Physics Institute The Russian Academy of Sciences Vavilov str. 38 Moscow119991 Russia School of Physics The University of Melbourne ParkvilleVIC3010 Australia Leipzig04318 Germany Universität Leipzig Felix Bloch Institute for Solid State Physics Applied Quantum Systems Leipzig04103 Germany QUANTUM Institut für Physik Johannes Gutenberg-Universität Mainz Mainz55128 Germany Department of Materials Science and Engineering University of Tennessee KnoxvilleTN37996 United States Paul Scherrer Institute Villigen5232 Switzerland Zürich8093 Switzerland Zyvex Labs 1301 N. Plano Road RichardsonTX75081 United States University of Texas DallasTX United States Sandia National Laboratories 1515 Eubank Blvd. SE AlbuquerqueNM87185 United States

Spin states in semiconductors provide exceptionally stable and noise-resistant environments for qubits, positioning them as optimal candidates for reliable quantum computing technologies. The proposal to use nuclear and electronic spins of donor atoms in silicon, introduced by Kane in 1998, sparked a new research field focused on the precise positioning of individual impurity atoms for quantum devices, utilising scanning tunnelling microscopy and ion implantation. This roadmap article reviews the advancements in the 25 years since Kane’s proposal, the current challenges, and the future directions in atomic-scale semiconductor device fabrication and measurement. It covers the quest to create a silicon-based quantum computer and expands to include diverse material systems and fabrication techniques, highlighting the potential for a broad range of semiconductor quantum technological applications. Key developments include phosphorus in silicon devices such as single-atom transistors, arrayed few-donor devices, one- and two-qubit gates, three-dimensional architectures, and the development of a toolbox for future quantum integrated circuits. The roadmap also explores new impurity species like arsenic and antimony for enhanced scalability and higher-dimensional spin systems, new chemistry for dopant precursors and lithographic resists, and the potential for germanium-based devices. Emerging methods, such as photon-based lithography and electron beam manipulation, are discussed for their disruptive potential. This roadmap charts the path toward scalable quantum computing and advanced semiconductor quantum technologies, emphasising the critical intersections of experiment, technological development, and theory. © 2025, CC BY.

关键词： Qubits

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Significance of the nonlocal optical response of metal nanoparticles in describing the operation of plasmonic lasers

引用

Physical Review B 2019年第11期99卷 115405-115405页

作者： Dasuni Lelwala Gamacharige Sarath D. Gunapala Mark I. Stockman Malin Premaratne Advanced Computing and Simulation Laboratory (AχL) Department of Electrical and Computer Systems Engineering Monash University Clayton Victoria 3800 Australia Jet Propulsion Laboratory California Institute of Technology Pasadena California 91109 USA Department of Physics and Astronomy Georgia State University Atlanta Georgia 30303 USA

A metal nanoparticle (MNP) coupled to a quantum emitter (QE) is a versatile composite nanostructure with unique chemical and physical properties which has been studied intensively, owing to its vast range of promising applications in nanoscience and nanotechnology. When pumped into a higher gain level, an MNP-QE composite nanostructure functions as a nanoplasmonic counterpart of a conventional laser, which is capable of operating at subwavelengths. The theory of plasmonic lasers is hitherto developed on the local optical response of the MNP, disregarding the nanoscale effects of its free electrons. In this paper, we perform a comprehensive quantum mechanical analysis of a complex MNP-QE composite nanostructure, capturing the size-dependent nonclassical effects through the nonlocal optical response of the MNP. Our study reveals that the nonlocal correction introduces significant deviations to the plasmon statistics of the hybrid particle suggested by the local calculations, becoming more prominent when the number of QEs coupled to the MNP increases. Furthermore, for the typical material parameter values used in the literature, we observed the initiation of quenching effects at lower pumping rates than suggested by the local response formalism. In essence, nonlocally assessed plasmon statistics of MNP-QE composite nanostructures demand the concerted coupling of an even higher number of QEs to compensate the deterioration in coherence and to sustain lasing.

关键词： Hybrid quantum systems Plasmonics Nanoparticles

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Cavity quantum electrodynamic analysis of spasing in nanospherical dimers

引用

Physical Review B 2019年第8期100卷 085439-085439页

作者： Tharindu Warnakula Sarath D. Gunapala Mark I. Stockman Malin Premaratne Advanced Computing and Simulation Laboratory (AXL) Department of Electrical and Computer Systems Engineering Monash University Clayton Victoria 3800 Australia Jet Propulsion Laboratory California Institute of Technology Pasadena California 91109 USA Department of Physics and Astronomy Georgia State University Atlanta Georgia 30303 USA

We present a detailed cavity quantum electrodynamic model of a nanospherical dimer and use it to analyze bright hybrid spasing modes there. Using an approximate numerical scheme, we model the complete spasing system as an open quantum system under the Lindblad dissipator formalism. We show that while in general the longitudinal dimer setups display higher intensity spasing as compared with transverse dimers, the latter actually consistently lead to output with higher coherence. Intriguingly, and somewhat counterintuitively, we find that transverse dimers only reach peak output at an intermediate dimer separation at which field confinement is not the strongest. We show that this is due to low radiative decay rates of transverse dimers with significant dimer gaps. We also find that transverse dimers outperform longitudinal dimers in terms of output intensity in a weakly pumped sparse gain medium made of dimers with relatively large separations. Moreover, in all the configurations considered, we find that the second-order coherence of the spasing output shows a peaked behavior just before the threshold, suggesting that the coherence is a useful indicator of spasing. Even though the scheme we describe is focused on dimers, owing to the generic form of the analysis presented, it can be easily extended to investigate spasing in the bright modes of multiple coupled plasmon sources.

关键词： Hybrid quantum systems Plasmonics Nanoparticles

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Federated variance-reduced stochastic gradient descent with robustness to Byzantine attacks

arXiv

引用

arXiv 2019年

作者： Wu, Zhaoxian Ling, Qing Chen, Tianyi Giannakis, Georgios B. School of Data and Computer Science Guangdong Province Key Laboratory of Computational Science Sun Yat-Sen University GuangzhouGuangdong510006 China Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute TroyNY12180 United States Department of Electrical and Computer Engineering Digital Technology Center University of Minnesota MinneapolisMN55455 United States

This paper deals with distributed finite-sum optimization for learning over networks in the presence of malicious Byzantine attacks. To cope with such attacks, most resilient approaches so far combine stochastic gradient descent (SGD) with different robust aggregation rules. However, the sizeable SGD-induced stochastic gradient noise makes it challenging to distinguish malicious messages sent by the Byzantine attackers from noisy stochastic gradients sent by the 'honest' workers. This motivates us to reduce the variance of stochastic gradients as a means of robustifying SGD in the presence of Byzantine attacks. To this end, the present work puts forth a Byzantine attack resilient distributed (Byrd-) SAGA approach for learning tasks involving finite-sum optimization over networks. Rather than the mean employed by distributed SAGA, the novel Byrd-SAGA relies on the geometric median to aggregate the corrected stochastic gradients sent by the workers. When less than half of the workers are Byzantine attackers, the robustness of geometric median to outliers enables Byrd-SAGA to attain provably linear convergence to a neighborhood of the optimal solution, with the asymptotic learning error determined by the number of Byzantine workers. Numerical tests corroborate the robustness to various Byzantine attacks, as well as the merits of Byrd-SAGA over Byzantine attack resilient distributed SGD. Copyright © 2019, The Authors. All rights reserved.

关键词： Optimization

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Resource allocation for physical-layer security in OFDMA downlink with imperfect CSI

引用

Frontiers of Information Technology & Electronic engineering 2018年第3期19卷 398-408页

作者： Wei YANG Jing MAO Chen CHEN Xiang CHENG Liu-qing YANG Hai-ge XIANG State Key Laboratory of Advanced Optical Communication Systems and Networks Peking University Department of Electrical & Computer Engineering Colorado State University

We investigate the problem of resource allocation in a downlink orthogonal frequency-division multiple access （OFDMA） broadband network with an eavesdropper under the condition that both legitimate users and the eavesdropper are with imperfect channel state information （CSI）. We consider three kinds of imperfect CSI：（1） noise and channel estimation errors, （2） feedback delay and channel prediction, and （3） limited feedback channel capacity, where quantized CSI is studied using rate-distortion theory because it can be used to establish an information-theoretic lower bound on the capacity of the feedback channel. The problem is formulated as joint power and subcarrier allocation to optimize the maximum-minimum （max-min） fairness criterion over the users＇ secrecy rate. The problem considered is a mixed integer nonlinear programming problem. To reduce the complexity, we propose a two-step suboptimal algorithm that separately performs power and subcarrier allocation. For a given subcarrier assignment, optimal power allocation is achieved by developing an algorithm of polynomial computational complexity. Numerical results show that our proposed algorithm can approximate the optimal solution.

关键词： Resource allocation Orthogonal frequency-division multiple access（OFDMA） Imperfect channel state information（CSI） Physical layer security

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Reversible engineering of topological insulator surface state conductivity through optical excitation

arXiv

引用

arXiv 2020年

作者： Xie, Faji Lian, Zhen Zhang, Shuai Wang, Tianmeng Miao, Shengnan Song, Zhiyong Ying, Zhe Pan, Xing-Chen Long, Mingsheng Zhang, Minhao Fei, Fucong Hu, Weida Yu, Geliang Song, Fengqi Kang, Ting-Ting Shi, Su-Fei National Laboratory of Solid State Microstructures School of Physics and Collaborative Innovation Center of Advanced Microstructures Nanjing University Nanjing210093 China Department of Chemical and Biological Engineering Rensselaer Polytechnic Institute TroyNY12810 United States State Key Laboratory of Infrared Physics Shanghai Institute of Technical Physics Chinese Academy of Sciences Shanghai200083 China Department of Electrical Computer & Systems Engineering Rensselaer Polytechnic Institute TroyNY12180 United States

Despite the broadband response, limited optical absorption at a particular wavelength hinders the development of optoelectronics based on Dirac fermions1,2. Heterostructures of graphene and various semiconductors have been explored for this purpose3, while non-ideal interfaces often limit the performance. The topological insulator is a natural hybrid system4-6, with the surface states hosting high-mobility Dirac fermions and the small-bandgap semiconducting bulk state strongly absorbing light. In this work, we show a large photocurrent response from a field effect transistor device based on intrinsic topological insulator Sn-Bi1.1Sb0.9Te2S. The photocurrent response is non-volatile and sensitively depends on the initial Fermi energy of the surface state, and it can be erased by controlling the gate voltage. Our observations can be explained with a remote photo-doping mechanism, in which the light excites the defects in the bulk and frees the localized carriers to the surface state. This photodoping modulates the surface state conductivity without compromising the mobility, and it also significantly modify the quantum Hall effect of the surface state. Our work thus illustrates a route to reversibly manipulate the surface states through optical excitation, shedding light into utilizing topological surface states for quantum optoelectronics. Copyright © 2020, The Authors. All rights reserved.

关键词： Surface states

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Blockchain for giving patients control over their medical records

TechRxiv

引用

TechRxiv 2020年

作者： Madine, Mohammad Battah, Ammar Yaqoob, Ibrar Salah, Khaled Jayaraman, Raja Al-Hammadi, Yousof Pesic, Sasa Ellahham, Samer The Department of Electrical Engineering and Computer Science Khalifa University Abu Dhabi127788 United Arab Emirates The Department of Industrial and Systems Engineering Khalifa University Abu Dhabi127788 United Arab Emirates ASU’s Blockchain Research Laboratory Arizona State University TempeAZ85281 United States Heart & Vascular Institute Cleveland Clinic Abu Dhabi Abu Dhabi United Arab Emirates

Personal health records (PHRs) are valuable assets to individuals because they enable them to integrate and manage their medical data. A PHR is an electronic application through which patients can manage their health information. Giving patients control over their medical data offers an advantageous realignment of the doctor-patient dynamic. However, today’s PHR management systems fall short of giving reliable, traceable, trustful, and secure patients control over their medical data, which poses serious threats to their authenticity and accuracy. Moreover, most of the current approaches and systems leveraged for managing PHR are centralized that not only make medical data sharing difficult but also poses a risk of single point of failure problem. In this paper, we propose Ethereum blockchain-based smart contracts to give patients control over their data in a manner that is decentralized, immutable, transparent, traceable, trustful, and secure. The proposed system employs decentralized storage of interplanetary file systems (IPFS), proxy re-encryption, and trusted reputation-based oracles to securely fetch, store, and share patients’ medical data. We present algorithms along with their full implementation details. We evaluate the proposed smart contracts using two important performance metrics, such as cost and correctness. Furthermore, we provide security analysis and discuss the generalization aspects of our solution. We outline the limitations of the proposed approach. We make the smart contract source code publicly available on Github. © 2020, CC BY.

关键词： Smart contract

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A Hybrid Approach for Weather-based Power Interruption Forecasting using Multilayer Perceptrons and Parametric Models

A Hybrid Approach for Weather-based Power Interruption Forec...

引用

IEEE PES Asia-Pacific Power and Energy engineering Conference (APPEEC)

作者： Longfei Wei Xiaolei Yang Guangyi Liu Renchang Dai Aditya Sundararajan Arif I. Sarwat Global Energy Interconnection Research Institute North America San Jose CA USA State Grid Sichuan Electric Power Company Chengdu Sichuan China Power and Energy Systems Group Oak Ridge National Laboratory Oak Ridge TN USA Department of Electrical & Computer Engineering Florida International University Miami FL USA

ISBN: (数字)9781728157481

ISBN: (纸本)9781728157498

This paper investigates the impact of various weather conditions on the reliability performance of power distribution networks. Especially, a hybrid approach based on multilayer perceptrons (MLPs) and parametric models is proposed to forecast the daily numbers of sustained and momentary power interruptions in the distribution management area using chronological weather data. First, the parametric regression models are implemented to analyze the relationship between power interruptions and different weather characteristics including temperature, wind speed, rain precipitation, air pressure, and lightning. The selected weather characteristics and corresponding parametric models are then integrated as inputs to formulate a MLP neural network model to forecast the daily numbers of power interruptions. In addition, a modified extreme learning machine (ELM) based hierarchical learning algorithm is introduced for training the formulated forecasting model. Finally, the real power interruption data collected from a Florida electric utility is used to verify the applicability and effectiveness of the proposed hybrid approach.

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