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arXiv 2019年

作者： Venzke, Andreas Chatzivasileiadis, Spyros Molzahn, Daniel K. Chatzivasileiadis Are with the Department of Electrical Engineering Technical University of Denmark Kgs. Lyngby2800 Denmark School of Electrical and Computer Engineering Georgia Institute of Technology AtlantaGA30313 United States Energy Systems Division Argonne National Laboratory LemontIL60439 United States

Convex relaxations of AC optimal power flow (ACOPF) problems have attracted significant interest as in several instances they provably yield the global optimum to the original non-convex problem. If, however, the relaxation is inexact, the obtained solution is not AC-feasible. The quality of the obtained solution is essential for several practical applications of AC-OPF, but detailed analyses are lacking in existing literature. This paper aims to cover this gap. We provide an in-depth investigation of the solution characteristics when convex relaxations are inexact, we assess the most promising AC feasibility recovery methods for large-scale systems, and we propose two new metrics that lead to a better understanding of the quality of the identified solutions. We perform a comprehensive assessment on 96 different test cases, ranging from 14 to 3120 buses, and we show the following: (i) Despite an optimality gap of less than 1%, several test cases still exhibit substantial distances to both AC feasibility and local optimality and the newly proposed metrics characterize these deviations. (ii) Penalization methods fail to recover an ACfeasible solution in 15 out of 45 cases, and using the proposed metrics, we show that most failed test instances exhibit substantial distances to both AC-feasibility and local optimality. For failed test instances with small distances, we show how our proposed metrics inform a fine-tuning of penalty weights to obtain ACfeasible solutions. (iii) The computational benefits of warmstarting non-convex solvers have significant variation, but a computational speedup exists in over 75% of the cases. Copyright © 2019, The Authors. All rights reserved.

关键词： Acoustic generators

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Electron energy relaxation in disordered superconducting NbN films

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Physical Review B 2020年第5期102卷 054501-054501页

作者： Mariia Sidorova Alexej Semenov Heinz-Wilhelm Hübers Konstantin Ilin Michael Siegel Ilya Charaev Maria Moshkova Natalia Kaurova Gregory N. Goltsman Xiaofu Zhang Andreas Schilling Institute of Optical Sensor Systems German Aerospace Center (DLR) Rutherfordstrasse 2 12489 Berlin Germany Department of Physics Faculty of Mathematics and Natural Sciences Humboldt University Berlin Unter den Linden 6 10099 Berlin Germany Institut für Mikro- und Nanoelektronische Systeme (IMS) Karlsruher Institut für Technologie (KIT) Hertzstrasse 16 76187 Karlsruhe Germany Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA HSE Tikhonov Moscow Institute of Electronics and Mathematics National Research University Higher School of Economics Tallinskaya Ulitsa34 123458 Moscow Russia Department of Physics Moscow Pedagogical State University 29 Malaya Pirogovskaya Street Moscow 119435 Russia Physics Institute University of Zürich Winterthurerstrasse 190 8057 Zürich Switzerland

We report on the inelastic-scattering rate of electrons on phonons and relaxation of electron energy studied by means of magnetoconductance, and photoresponse, respectively, in a series of strongly disordered superconducting NbN films. The studied films with thicknesses in the range from 3 to 33 nm are characterized by different Ioffe-Regel parameters but an almost constant product qTl (qT is the wave vector of thermal phonons and l is the elastic mean free path of electrons). In the temperature range 14–30 K, the electron-phonon scattering rates obey temperature dependencies close to the power law 1/τe−ph∼Tn with the exponents n≈3.2–3.8. We found that in this temperature range τe−ph and n of studied films vary weakly with the thickness and square resistance. At 10 K electron-phonon scattering times are in the range 11.9–17.5 ps. The data extracted from magnetoconductance measurements were used to describe the experimental photoresponse with the two-temperature model. For thick films, the photoresponse is reasonably well described without fitting parameters, however, for thinner films, the fit requires a smaller heat capacity of phonons. We attribute this finding to the reduced density of phonon states in thin films at low temperatures. We also show that the estimated Debye temperature in the studied NbN films is noticeably smaller than in bulk material.

关键词： Acoustic phonons Electron relaxation Heat transfer Magnetotransport Superconductivity

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2022 Roadmap on Neuromorphic Computing and engineering

arXiv

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arXiv 2021年

作者： Christensen, Dennis Valbjørn Dittmann, Regina Linares-Barranco, Bernabé Sebastian, Abu Le Gallo, Manuel Redaelli, Andrea Slesazeck, Stefan Mikolajick, Thomas Spiga, Sabina Menzel, Stephan Valov, Ilia Milano, Gianluca Ricciardi, Carlo Liang, Shi-Jun Miao, Feng Lanza, Mario Quill, Tyler J. Keene, Scott T. Salleo, Alberto Grollier, Julie Marković, Danijela Mizrahi, Alice Yao, Peng Yang, J. Joshua Indiveri, Giacomo Strachan, John Paul Datta, Suman Vianello, Elisa Valentian, Alexandre Feldmann, Johannes Li, Xuan Pernice, Wolfram H.P. Bhaskaran, Harish Furber, Steve Neftci, Emre Scherr, Franz Maass, Wolfgang Ramaswamy, Srikanth Tapson, Jonathan Panda, Priyadarshini Kim, Youngeun Tanaka, Gouhei Thorpe, Simon Bartolozzi, Chiara Cleland, Thomas A. Posch, Christoph Liu, Shih-Chii Panuccio, Gabriella Mahmud, Mufti Mazumder, Arnab Neelim Hosseini, Morteza Mohsenin, Tinoosh Donati, Elisa Tolu, Silvia Galeazzi, Roberto Christensen, Martin Ejsing Holm, Sune Ielmini, Daniele Pryds, N. Department of Energy Conversion and Storage Technical University of Denmark Kgs. LyngbyDK-2800 Denmark Peter Gruenberg Institute 7 Forschungszentrum Juelich GmbH Juelich52425 Germany JARA-FIT RWTH Aachen University Aachen52056 Germany CSIC Universidad de Sevilla Seville41092 Spain IBM Research Zurich Switzerland STMicroelectronics Agrate Italy Dresden01187 Germany Institute of Semiconductors and Microsystems TU Dresden Dresden Germany CNR-IMM Unit of Agrate Brianza via C. Olivetti 2 MB Agrate Brianza Italy Juelich Germany Torino Italy Department of Applied Science and Technology Politecnico di Torino Torino Italy National Laboratory of Solid State Microstructures School of Physics Collaborative Innovation Center of Advanced Microstructures Nanjing University Nanjing China Thuwal23955-6900 Saudi Arabia Department of Materials Science and Engineering Stanford University StanfordCA94305 United States Department of Engineering University of Cambridge CambridgeCB2 1PZ United Kingdom Unité Mixte de Physique CNRS Thales Université Paris-Saclay Palaiseau91767 France Electrical and Computer Engineering Department University of Southern California Los AngelesCA United States Institute of Neuroinformatics University of Zurich ETH Zurich Switzerland Hewlett Packard Laboratories Hewlett Packard Enterprise San JoseCA United States Department of Electrical Engineering University of Notre Dame Notre DameIN United States CEA LETI Université Grenoble Alpes Grenoble France CEA LIST Université Grenoble Alpes Grenoble France Department of Materials University of Oxford Parks Road OxfordOX1 3PH United Kingdom Institute of Physics University of Münster Heisenbergstr. 11 Heisenbergstr Münster48149 Germany Center for Soft Nanoscience University of Münster Münster48149 Germany The University of Manchester United Kingdom Department of Cognitive Sciences University of California Irvine IrvineCA United States Institute of Theoretica

Modern computation based on the von Neumann architecture is today a mature cutting-edge science. In the Von Neumann architecture, processing and memory units are implemented as separate blocks interchanging data intensively and continuously. This data transfer is responsible for a large part of the power consumption. The next generation computer technology is expected to solve problems at the exascale with 1018 calculations each second. Even though these future computers will be incredibly powerful, if they are based on von Neumann type architectures, they will consume between 20 and 30 megawatts of power and will not have intrinsic physically built-in capabilities to learn or deal with complex data as our brain does. These needs can be addressed by neuromorphic computing systems which are inspired by the biological concepts of the human brain. This new generation of computers has the potential to be used for the storage and processing of large amounts of digital information with much lower power consumption than conventional processors. Among their potential future applications, an important niche is moving the control from data centers to edge devices. The aim of this Roadmap is to present a snapshot of the present state of neuromorphic technology and provide an opinion on the challenges and opportunities that the future holds in the major areas of neuromorphic technology, namely materials, devices, neuromorphic circuits, neuromorphic algorithms, applications, and ethics. The Roadmap is a collection of perspectives where leading researchers in the neuromorphic community provide their own view about the current state and the future challenges for each research area. We hope that this Roadmap will be a useful resource by providing a concise yet comprehensive introduction to readers outside this field, for those who are just entering the field, as well as providing future perspectives for those who are well established in the neuromorphic computing community. © 2021,

关键词： Data transfer

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Quantum Noise Theory of Exceptional Point Amplifying Sensors

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Physical Review Letters 2019年第18期123卷 180501-180501页

作者： Mengzhen Zhang William Sweeney Chia Wei Hsu Lan Yang A. D. Stone Liang Jiang Departments of Applied Physics and Physics Yale University New Haven Connecticut 06520 USA Yale Quantum Institute Yale University New Haven Connecticut 06520 USA Ming Hsieh Department of Electrical and Computer Engineering University of Southern California Los Angeles California 90089 USA Department of Electrical and Systems Engineering Washington University St Louis Missouri 63130 USA Pritzker School of Molecular Engineering The University of Chicago Chicago Illinois 60637 USA

Open quantum systems can have exceptional points (EPs), degeneracies where both eigenvalues and eigenvectors coalesce. Recently, it has been proposed and demonstrated that EPs can enhance the performance of sensors in terms of amplification of a detected signal. However, typically amplification of signals also increases the system noise, and it has not yet been shown that an EP sensor can have improved signal-to-noise performance. We develop a quantum noise theory to calculate the signal-to-noise performance of an EP sensor. We use the quantum Fisher information to extract a lower bound for the signal-to-noise ratio (SNR) and show that parametrically improved SNR is possible. Finally, we construct a specific experimental protocol for sensing using an EP amplifier near its lasing threshold and heterodyne signal detection that achieves the optimal scaling predicted by the Fisher bound. Our results can be generalized to higher order EPs for any bosonic non-Hermitian system with linear interactions.

关键词： Electromagnetism Metrology PT-symmetric quantum mechanics Quantum metrology

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Chemical Reactions-based Detection Mechanism for Molecular Communications

arXiv

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arXiv 2019年

作者： Cao, Trang Ngoc Jamali, Vahid Wicke, Wayan Zlatanov, Nikola Yeoh, Phee Lep Evans, Jamie S. Schober, Robert The School of Psychological Sciences Monash University MelbourneVIC3800 Australia The Department of Electrical and Computer Princeton University NJ08544 United States The Institute for Digital Communications Friedrich-Alexander- Universität Erlangen-Nürnberg Erlangen91058 Germany The Department of Electrical and Computer Systems Engineering Monash University MelbourneVIC3800 Australia The School of Electrical and Information Engineering University of Sydney SydneyNSW2006 Australia The Department of Electrical and Electronic Engineering University of Melbourne MelbourneVIC3010 Australia

In molecular communications, the direct detection of signaling molecules may be challenging due to a lack of suitable sensors and interference from co-existing substances in the environment. Motivated by research in molecular biology, we investigate an indirect detection mechanism using chemical reactions between the signaling molecules and a molecular probe to produce an easy-to-measure product at the receiver. We consider two implementations of the proposed detection mechanism, i.e., unrestricted probe movement and probes restricted to a volume around the receiver. In general, the resulting reaction-diffusion equations that describe the concentrations of the reactant and product molecules in the system are non-linear and coupled, and cannot be solved in closed form. To evaluate these molecule concentrations, we develop an efficient iterative algorithm by discretizing the time variable and solving for the space variables of the concentration equations in each time step. The accuracy of our proposed algorithm is verified by particle-based simulations. In the special case when the concentration of the unrestricted probes is high and not changed significantly by the chemical reaction compared to the signaling molecule concentration, we can obtain insightful closed-form solutions. Our results show that the concentrations of the product molecules and the signalling molecules share a similar characteristic over time, i.e., a single peak and a long tail. The peak and tail values of the product molecule concentration can be controlled by choosing probes with suitable parameters, e.g., the diffusion coefficient, reaction rate, and released quantity. We analyze the bit error rate (BER) of the system for a threshold decision rule. Furthermore, we highlight that by carefully choosing the molecular probe and optimizing the decision threshold, the BER can be improved significantly and outperform that of a direct detection system. Moreover, when molecular probes are kept in a sma

关键词： Probes

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Meta-transfer learning through hard tasks

arXiv

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arXiv 2019年

作者： Sun, Qianru Liu, Yaoyao Chen, Zhaozheng Chua, Tat-Seng Schiele, Bernt School of Information Systems Singapore Management University School of Electrical and Information Engineering Tianjin University School of Computing National University of Singapore Department of Computer Vision and Machine Learning Max-Plank Institute for Informatics

Meta-learning has been proposed as a framework to address the challenging few-shot learning setting. The key idea is to leverage a large number of similar few-shot tasks in order to learn how to adapt a base-learner to a new task for which only a few labeled samples are available. As deep neural networks (DNNs) tend to overfit using a few samples only, typical meta-learning models use shallow neural networks, thus limiting its effectiveness. In order to achieve top performance, some recent works tried to use the DNNs pre-trained on large-scale datasets but mostly in straight-forward manners, e.g., (1) taking their weights as a warm start of meta-training, and (2) freezing their convolutional layers as the feature extractor of base-learners. In this paper, we propose a novel approach called meta-transfer learning (MTL) which learns to transfer the weights of a deep NN for few-shot learning tasks. Specifically, meta refers to training multiple tasks, and transfer is achieved by learning scaling and shifting functions of DNN weights for each task. In addition, we introduce the hard task (HT) meta-batch scheme as an effective learning curriculum that further boosts the learning efficiency of MTL. We conduct few-shot learning experiments and report top performance for five-class few-shot recognition tasks on three challenging benchmarks: miniImageNet, tieredImageNet and Fewshot-CIFAR100 (FC100). Extensive comparisons to related works validate that our MTL approach trained with the proposed HT meta-batch scheme achieves top performance. An ablation study also shows that both components contribute to fast convergence and high accuracy. Compared to the conference version of the paper [1], this version additionally presents (1) the analysis of using different DNN architectures, e.g., ResNet-12, ResNet-18 and ResNet-25;(2) the new MTL variants that adapt our scaling and shifting functions to the classical supervised and the state-of-the-art semi-supervised meta-learners, and

关键词： Deep neural networks

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Analysis of a canonical labeling algorithm for the alignment of correlated Erdos-Rényi graphs

arXiv

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arXiv 2018年

作者： Dai, Osman Emre Cullina, Daniel Kiyavash, Negar Grossglauser, Matthias Georgia Institute of Technology Department of Industrial & Systems Engineering Princeton University Department of Electrical Engineering Georgia Institute of Technology Department of Electrical and Computer Engineering Department of Industrial & Systems Engineering

Graph alignment in two correlated random graphs refers to the task of identifying the correspondence between vertex sets of the graphs. Recent results have characterized the exact information-theoretic threshold for graph alignment in correlated Erdos-Rényi graphs. However, very little is known about the existence of efficient algorithms to achieve graph alignment without seeds. In this work we identify a region in which a straightforward O(n11/5 log n)-time canonical labeling algorithm, initially introduced in the context of graph isomorphism, succeeds in aligning correlated Eros-Rényi graphs. The algorithm has two steps. In the first step, all vertices are labeled by their degrees and a trivial minimum distance alignment (i.e., sorting vertices according to their degrees) matches a fixed number of highest degree vertices in the two graphs. Having identified this subset of vertices, the remaining vertices are matched using a alignment algorithm for bipartite graphs. Copyright © 2018, The Authors. All rights reserved.

关键词： Graphic methods

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Correction to: MEMS-actuated metasurface Alvarez lens

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Microsystems & nanoengineering 2021年第1期7卷 12页

作者： Zheyi Han Shane Colburn Arka Majumdar Karl F Böhringer Department of Electrical and Computer Engineering University of Washington Seattle WA 98195 USA. Institute for Nano-Engineered Systems University of Washington Seattle WA 98195 USA. Department of Physics University of Washington Seattle WA 98195 USA. Department of Bioengineering University of Washington Seattle WA 98195 USA.

[This corrects the article DOI: 10.1038/s41378-020-00190-6.].

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Associations between Aβ deposition and neurometabolic alterations in Alzheimer's disease: Insights from hybrid 3D MRSI-PET imaging

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Alzheimer's & dementia : the journal of the Alzheimer's Association 2025年第6期21卷 e70332页

作者： Miao Zhang Jialin Hu Yaoyu Zhang Ziyu Meng Yibo Zhao Yudu Li Wen Jin Xiao-Hang Qian Lijun Wang Guanyu Ye Xu-Feng Jiang Ya-Dong Li Jian Ye Huidong Tang Jun Liu Parashkev Nachev Zhi-Pei Liang Biao Li Yao Li Department of Nuclear Medicine Ruijin Hospital School of Biomedical Engineering Shanghai Jiao Tong University Shanghai China. National Engineering Research Center of Advanced Magnetic Resonance Technologies for Diagnosis and Therapy Shanghai Jiao Tong University Shanghai China. Institute of Medical Robotics Shanghai Jiao Tong University Shanghai China. Beckman Institute for Advanced Science and Technology University of Illinois at Urbana-Champaign Urbana Illinois USA. Department of Electrical and Computer Engineering University of Illinois at Urbana-Champaign Urbana Illinois USA. National Center for Supercomputing Applications University of Illinois at Urbana-Champaign Urbana Illinois USA. Department of Geriatrics Ruijin Hospital Shanghai Jiao Tong University School of Medicine Shanghai China. Medical Center on Aging of Ruijin Hospital Shanghai Jiao Tong University School of Medicine Shanghai China. Department of Neurology and Institute of Neurology Ruijin Hospital Shanghai Jiao Tong University School of Medicine Shanghai China. Department of Neurovascular Center Changhai Hospital Naval Medical University Shanghai China. Department of Gastroenterology Songjiang Hospital and Songjiang Research Institute Shanghai Key Laboratory of Emotions and Affective Disorders State Key Laboratory of Eye Health Shanghai Jiao Tong University School of Medicine Shanghai China. Shanghai Key Laboratory of Gynecologic Oncology Renji Hospital School of Medicine Shanghai Jiao Tong University Shanghai China. High-Dimensional Neurology Group Institute of Neurology University College London London UK.

INTRODUCTION:Understanding the neurometabolic changes associated with amyloid-β (Aβ) deposition is important for early Alzheimer's disease (AD) diagnosis, but their spatial relationships remained unexplored due to technical limitations. METHODS:We investigated the relationship between Aβ deposition and neuronal and glial metabolites using high-resolution 3D magnetic resonance spectroscopic imaging (MRSI) (8-min scan, 2 × 3 × 3 mm resolution) and Aβ-positron emission tomography (Aβ-PET) imaging. N-acetylaspartate, myo-inositol, and creatine maps were obtained from 174 participants: 39 controls, 65 mild cognitive impairment (MCI), and 70 AD patients. RESULTS:N-Acetylaspartate levels were negatively correlated with Aβ, while myo-inositol levels were positively correlated globally. Regional associations with Aβ include N-acetylaspartate reductions in frontal cortex, anterior cingulate cortex, and precuneus, and myo-inositol increases in precuneus, lateral temporal, and lateral parietal cortices. Combined MRSI and PET biomarkers achieved the highest diagnostic accuracy for MCI and AD . DISCUSSION:Hybrid high-resolution 3D MRSI and Aβ-PET imaging provides valuable insights into Aβ's impact on neurometabolic changes, improving early AD diagnosis. HIGHLIGHTS:Hybrid 3D magnetic resonance spectroscopic imaging-positron emission tomography (MRSI-PET) imaging reveals Aβ deposition impact on neurometabolism in Alzheimer's disease (AD). N-acetylaspartate (NAA) as a neuronal metabolic marker is negatively associated with Aβ globally and locally. Myo-inositol (mI) as a glial metabolic marker is positively associated with Aβ globally and locally. Combining 3D magnetic resonance spectroscopic imaging (MRSI) and PET biomarkers improves diagnostic accuracy for mild cognitive impairment (MCI) and AD.

关键词： alzheimer's disease amyloid‐β magnetic resonance spectroscopic imaging myo‐inositol n‐acetylaspartate

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Power system state estimation via feasible point pursuit: Algorithms and Cramér-rao bound

Power system state estimation via feasible point pursuit: Al...

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作者： Wang, Gang Zamzam, Ahmed S. Giannakis, Georgios B. Sidiropoulos, Nicholas D. State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing100081 China Digital Technology Center Department of Electrical and Computer Engineering University of Minnesota MinneapolisMN55455 United States Department of Electrical and Computer Engineering University of Virginia CharlottesvilleVA22904 United States

Accurately monitoring the system's operating point is central to the reliable and economic operation of an autonomous energy grid. Power system state estimation (PSSE) aims to obtain complete voltage magnitude and angle information at each bus given a number of system variables at selected buses and lines. Power flow analysis amounts to solving a set of noise-free power flow equations, and is cast as a special case of PSSE. Physical laws dictate quadratic relationships between available quantities and unknown voltages, rendering general instances of power flow and PSSE nonconvex and NP-hard. Past approaches are largely based on gradient-type iterative procedures or semidefinite relaxation (SDR). Due to nonconvexity, the solution obtained via gradient-type schemes depends on initialization, while SDR methods do not perform as desired in challenging scenarios. This paper puts forth novel feasible point pursuit (FPP)-based solvers for power flow analysis and PSSE, which iteratively seek feasible solutions for a nonconvex quadratically constrained quadratic programming reformulation of the weighted least-squares (WLS). Relative to the prior art, the developed solvers offer superior numerical performance at the cost of higher computational complexity. Furthermore, they converge to a stationary point of the WLS problem. As a baseline for comparing different estimators, the Cramér-Rao lower bound is derived for the fundamental PSSE problem in this paper. Judicious numerical tests on several IEEE benchmark systems showcase markedly improved performance of our FPP-based solvers for both power flow and PSSE tasks over popular WLS-based Gauss-Newton iterations and SDR approaches. © 1991-2012 IEEE.

关键词： State estimation

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