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European Signal Processing Conference

作者： Anthony Griffin Nicolas Pradel Brody Radford David I. Wilson Andrew Ensor Electrical and Electronic Engineering Department Mathematical Sciences Department High Performance Computing Research Laboratory Computer Science Department Auckland University of Technology New Zealand

In this paper we present our end-to-end model of the imaging pipeline in the Square Kilometre Array. Our Sky Generator models the signals that are received by the Central Signal Processor (CSP), our CSP Correlator model then processes those signals to generate visibilities to pass to the science Data Processor (SDP). Our SDP Imaging model then grids the visibilities and inverse Fourier transforms them to produce a dirty image of the sky. Our modelling allows us to investigate the error that is introduced due to reduced numerical precision, and we then propose techniques to mitigate this error, and thus reduce the required amount of computational hardware.

关键词： Mathematical model Delays Antenna arrays Correlators Imaging Computational modeling

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Fault diagnosis for multi-energy flows of energy internet: Framework and prospects

Fault diagnosis for multi-energy flows of energy internet: F...

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2017 IEEE Conference on Energy Internet and Energy System Integration, EI2 2017

作者： Wang, Tao Wang, Jun Fan, Zhennan Wei, Xiaoguang Zang, Tianlei Pérez-Jiménez, Mario J. Huang, Tao School of Electrical Engineering and Electronic Information Sichuan Province Key Laboratory of Power Electronics Energy-saving Technologies and Equipment Key Laboratory of Fluid and Power Machinery Ministry of Education Xihua University Chengdu China School of Electrical Engineering Southwest Jiaotong University Chengdu China State Key Laboratory of Security Control and Simulation of Power Systems and Large Scale Generation Department of Electrical Engineering Tsinghua University Beijing China Research Groupon Natural Computing Department of Computer Science and Artificial Intelligence University of Sevilla Sevilla Spain Department of Energy Politecnico di Torino Torino Italy

ISBN: (纸本)9781538614273

Energy Internet (EI) is an inevitable development trend of energy systems under the background of technology development, environmental pressure and energy transition. Multi-energy flow coupling is one of the key characteristics of the EI, which enhances the interoperability of different types of energy flows while consequently increases the probability of cascading failures. Therefore it is of great significance to study the multi-energy flow fault diagnosis of the EI to ensure its safe and stable operation as well as the continuous energy supply. This paper introduces the concept of multi-energy flow cascading fault of the EI for the first time. The energy internet framework for multi-energy flow cascading fault diagnosis is firstly proposed, and then characteristics of various energy networks in the EI are analyzed from the perspective of fault diagnosis. Finally, future research prospects are discussed. © 2017 IEEE.

关键词： Failure analysis

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Spectrally multiplexed upconversion single-photon detection with C-band pump and signal wavelengths

Spectrally multiplexed upconversion single-photon detection ...

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Frontiers in Optics, FiO 2017

作者： Silver, Michael Velev, Vesselin G. Langrock, Carsten Fejer, Martin M. Kumar, Prem Kanter, Gregory S. Center for Photonic Communication and Computing Department of Electrical Engineering and Computer Science Northwestern University EvanstonIL60208 United States Department of Physics and Astronomy Northwestern University EvanstonIL60208 United States E. L. Ginzton Laboratory Stanford University StanfordCA94305 United States

We demonstrate low noise, spectrally multiplexed, upconversion single-photon detection using a waveguide with multiple phase-matching peaks. Two signal wavelengths are upconverted using two distinct pump wavelengths, ... 详细信息

ISBN: (纸本)9781943580330

关键词： Phase matching

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Conditional gradient method for stochastic submodular maximization: Closing the gap

arXiv

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arXiv 2017年

作者： Mokhtari, Aryan Hassani, Hamed Karbasi, Amin Laboratory for Information and Decision Systems MIT Simons Institute for the Theory of Computing University of California Berkeley Department of Electrical and Systems Engineering University of Pennsylvania Department of Electrical Engineering and Computer Science Yale University

In this paper, we study the problem of constrained and stochastic continuous submodular maximization. Even though the objective function is not concave (nor convex) and is defined in terms of an expectation, we develop a variant of the conditional gradient method, called Stochastic Continuous Greedy, which achieves a tight approximation guarantee. More precisely, for a monotone and continuous DR-submodular function and subject to a general convex body constraint, we prove that Stochastic Continuous Greedy achieves a [(1 - 1/e)OPT - ϵ] guarantee (in expectation) with O(1/ϵ3) stochastic gradient computations. This guarantee matches the known hardness results and closes the gap between deterministic and stochastic continuous submodular maximization. By using stochastic continuous optimization as an interface, we also provide the first (1-1/e) tight approximation guarantee for maximizing a monotone but stochastic submodular set function subject to a general matroid constraint. Copyright © 2017, The Authors. All rights reserved.

关键词： Stochastic systems

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Quantum key distribution with distinguishable decoy states

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Physical Review A 2018年第1期98卷 012330-012330页

作者： Anqi Huang Shi-Hai Sun Zhihong Liu Vadim Makarov Institute for Quantum Information & State Key Laboratory of High Performance Computing College of Computer National University of Defense Technology Changsha 410073 People's Republic of China Institute for Quantum Computing University of Waterloo Waterloo Ontario N2L 3G1 Canada Department of Electrical and Computer Engineering University of Waterloo Waterloo Ontario N2L 3G1 Canada College of Science National University of Defense Technology Changsha 410073 People's Republic of China College of Mechatronic Engineering and Automation National University of Defense Technology Changsha 410073 People's Republic of China Russian Quantum Center and MISIS University Moscow Department of Physics and Astronomy University of Waterloo Waterloo Ontario N2L 3G1 Canada

The decoy-state protocol has been considered to be one of the most important methods to protect the security of quantum key distribution (QKD) with a weak coherent source. Here we test two experimental approaches to generating the decoy states with different intensities: modulation of the pump current of a semiconductor laser diode, and external modulation by an optical intensity modulator. The former approach shows a side channel in the time domain that allows an attacker to distinguish s signal state from a decoy state, breaking a basic assumption in the protocol. We model a photon-number-splitting attack based on our experimental data, and show that it compromises the system's security. Then, based on the work of Tamaki et al. [New J. Phys. 18, 065008 (2016)], we obtain two analytical formulas to estimate the yield and error rate of single-photon pulses when the signal and decoy states are distinguishable. The distinguishability reduces the secure key rate below that of a perfect decoy-state protocol. To mitigate this reduction, we propose to calibrate the transmittance of the receiver (Bob's) unit. We apply our method to three QKD systems and estimate their secure key rates.

关键词： Quantum communication Quantum cryptography

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Towards the manipulation of topological states of matter: A perspective from electron transport

arXiv

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arXiv 2018年

作者： Zhang, Cheng Lu, Hai-Zhou Shen, Shun-Qing Chen, Yong P. Xiu, Faxian State Key Laboratory of Surface Physics and Department of Physics Fudan University Shanghai200433 China Collaborative Innovation Center of Advanced Microstructures Nanjing210093 China Institute for Quantum Science and Engineering Department of Physics South University of Science and Technology of China Shenzhen518055 China Shenzhen Key Laboratory of Quantum Science and Engineering Shenzhen518055 China Department of Physics University of Hong Kong Pokfulam Road Hong Kong Department of Physics and Astronomy Purdue University West LafayetteIN47907 United States Birck Nanotechnology Center Purdue University West LafayetteIN47907 United States School of Electrical and Computer Engineering Purdue University West LafayetteIN47907 United States Institute for Nanoelectronic Devices and Quantum Computing Fudan University Shanghai200433 China

The introduction of topological invariants, ranging from insulators to metals, has provided new insights into the traditional classification of electronic states in condensed matter physics. A sudden change in the topological invariant at the boundary of a topological nontrivial system leads to the formation of exotic surface states that are dramatically different from its bulk. In recent years, significant advancements in the exploration of the physical properties of these topological systems and regarding device research related to spintronics and quantum computation have been made. Here, we review the progress of the characterization and manipulation of topological phases from the electron transport perspective and also the intriguing chiral/Majorana states that stem from them. We then discuss the future directions of research into these topological states and their potential applications. Copyright © 2018, The Authors. All rights reserved.

关键词： Electron transport properties

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Large-Capacity Three-Party Quantum Digital Secret Sharing Using Three Particular Matrices Coding

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Communications in Theoretical Physics 2016年第11期65卷 501-508页

作者：赖红罗明星 Josef Pieprzyk 陶丽刘志明 Mehmet A.Orgun School of Computer and Information Science Southwest University Information Security and National Computing Grid Laboratory School of Information Science and TechnologySouthwest Jiaotong University School of Electrical Engineering and Computer Science Queensland University of Technology Institute of Computer Science Polish Academy of Sciences Department of Computing Macquarie University Faculty of Information Technology Macao University of Science and Technology

In this paper, we develop a large-capacity quantum digital secret sharing(QDSS) scheme, combined the Fibonacci- and Lucas-valued orbital angular momentum(OAM) entanglement with the recursive Fibonacci and Lucas matrices. To be exact, Alice prepares pairs of photons in the Fibonacci- and Lucas-valued OAM entangled states, and then allocates them to two participants, say, Bob and Charlie, to establish the secret key. Moreover, the available Fibonacci and Lucas values from the matching entangled states are used as the seed for generating the Fibonacci and Lucas matrices. This is achieved because the entries of the Fibonacci and Lucas matrices are recursive. The secret key can only be obtained jointly by Bob and Charlie, who can further recover the secret. Its security is based on the facts that nonorthogonal states are indistinguishable, and Bob or Charlie detects a Fibonacci number, there is still a twofold uncertainty for Charlie'(Bob') detected value.

关键词： Fibonacci-and Lucas-valued orbital angular momentum(OAM) states the first kind of Chebyshev maps lower error rates longer destances

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The Liver Tumor Segmentation Benchmark (LiTS)

arXiv

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arXiv 2019年

作者： Bilic, Patrick Christ, Patrick Li, Hongwei Bran Vorontsov, Eugene Ben-Cohen, Avi Kaissis, Georgios Szeskin, Adi Jacobs, Colin Mamani, Gabriel Efrain Humpire Chartrand, Gabriel Lohöfer, Fabian Holch, Julian Walter Sommer, Wieland Hofmann, Felix Hostettler, Alexandre Lev-Cohain, Naama Drozdzal, Michal Amitai, Michal Marianne Vivanti, Refael Sosna, Jacob Ezhov, Ivan Sekuboyina, Anjany Navarro, Fernando Kofler, Florian Paetzold, Johannes C. Shit, Suprosanna Hu, Xiaobin Lipková, Jana Rempfler, Markus Piraud, Marie Kirschke, Jan Wiestler, Benedikt Zhang, Zhiheng Hülsemeyer, Christian Beetz, Marcel Ettlinger, Florian Antonelli, Michela Bae, Woong Bellver, Míriam Bi, Lei Chen, Hao Chlebus, Grzegorz Dam, Erik B. Dou, Qi Fu, Chi-Wing Georgescu, Bogdan Giró-I-Nieto, Xavier Gruen, Felix Han, Xu Heng, Pheng-Ann Hesser, Jürgen Moltz, Jan Hendrik Igel, Christian Isensee, Fabian Jäger, Paul Jia, Fucang Kaluva, Krishna Chaitanya Khened, Mahendra Kim, Ildoo Kim, Jae-Hun Kim, Sungwoong Kohl, Simon Konopczynski, Tomasz Kori, Avinash Krishnamurthi, Ganapathy Li, Fan Li, Hongchao Li, Junbo Li, Xiaomeng Lowengrub, John Ma, Jun Maier-Hein, Klaus Maninis, Kevis-Kokitsi Meine, Hans Merhof, Dorit Pai, Akshay Perslev, Mathias Petersen, Jens Pont-Tuset, Jordi Qi, Jin Qi, Xiaojuan Rippel, Oliver Roth, Karsten Sarasua, Ignacio Schenk, Andrea Shen, Zengming Torres, Jordi Wachinger, Christian Wang, Chunliang Weninger, Leon Wu, Jianrong Xu, Daguang Yang, Xiaoping Yu, Simon Chun-Ho Yuan, Yading Yue, Miao Zhang, Liping Cardoso, Jorge Bakas, Spyridon Braren, Rickmer Heinemann, Volker Pal, Christopher Tang, An Kadoury, Samuel Soler, Luc van Ginneken, Bram Greenspan, Hayit Joskowicz, Leo Menze, Bjoern Department of Informatics Technical University of Munich Germany Department of Quantitative Biomedicine University of Zurich Switzerland Ecole Polytechnique de Montréal Canada Department of Medical Imaging Radboud University Medical Center Nijmegen Netherlands Department of Biomedical Engineering Tel-Aviv University Israel Germany Pattern Analysis and Learning Group Department of Radiation Oncology Heidelberg University Hospital Heidelberg Germany Philips Research China Philips China Innovation Campus Shanghai China School of Biomedical Engineering & Imaging Sciences King0s College London London United Kingdom Institute for AI in Medicine Technical University of Munich Germany Department of Computer Science Guangdong University of Foreign Studies China Institute for diagnostic and interventional radiology Klinikum rechts der Isar Technical University of Munich Germany Institute for Diagnostic and Interventional Neuroradiology Klinikum Rechts der Isar Technical University of Munich Germany Department of Hepatobiliary Surgery The Affiliated Drum Tower Hospital Nanjing University Medical School China Department of Computing Imperial College London London United Kingdom Institute for Tissue Engineering and Regenerative Medicine Helmholtz Zentrum München Neuherberg Germany Brigham and Women's Hospital Harvard Medical School United States School of Computer Science and Engineering The Hebrew University of Jerusalem Israel University of Pennsylvania PA United States Pte. Ltd. Singapore Medical Imaging and Reconstruction Lab Department of Engineering Design Indian Institute of Technology Madras India Sensetime Shanghai China Department of Radiology Perelman School of Medicine University of Pennsylvania United States Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania PA United States Co. Ltd China MontréalQC Canada Department of Radiology Radiation Oncology and Nuclear Medicine University of Montréal

In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark (LiTS), which was organized in conjunction with the IEEE International Symposium on Biomedical Imaging (ISBI) 2017 and the International Conferences on Medical Image computing and computer-Assisted Intervention (MICCAI) 2017 and 2018. The image dataset is diverse and contains primary and secondary tumors with varied sizes and appearances with various lesion-to-background levels (hyper-/hypo-dense), created in collaboration with seven hospitals and research institutions. Seventy-five submitted liver and liver tumor segmentation algorithms were trained on a set of 131 computed tomography (CT) volumes and were tested on 70 unseen test images acquired from different patients. We found that not a single algorithm performed best for both liver and liver tumors in the three events. The best liver segmentation algorithm achieved a Dice score of 0.963, whereas, for tumor segmentation, the best algorithms achieved Dices scores of 0.674 (ISBI 2017), 0.702 (MICCAI 2017), and 0.739 (MICCAI 2018). Retrospectively, we performed additional analysis on liver tumor detection and revealed that not all top-performing segmentation algorithms worked well for tumor detection. The best liver tumor detection method achieved a lesion-wise recall of 0.458 (ISBI 2017), 0.515 (MICCAI 2017), and 0.554 (MICCAI 2018), indicating the need for further research. LiTS remains an active benchmark and resource for research, e.g., contributing the liver-related segmentation tasks in http://***/. In addition, both data and online evaluation are accessible via ***. © 2019, CC BY-NC-ND.

关键词： Deep learning

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Accelerated quantum walk, two-particle entanglement generation and localization

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Journal of Physics Communications 2019年第5期3卷 055008-055008页

作者： Singh, Shivani Balu, Radhakrishnan Laflamme, Raymond Chandrashekar, C.M. The Institute of Mathematical Sciences C. I. T Campus Taramani Chennai 600113 India Homi Bhabha National Institute Training School Complex Anushakti Nagar Mumbai 400094 India U.S. Army Research Laboratory Adelphi 20783 MD United States Computer Science and Electrical Engineering University of Maryland Baltimore County 1000 Hilltop Circle Baltimore 21250 MD United States Institute for Quantum Computing Department of Physics and Astronomy University of Waterloo Waterloo N2L 3G1 ON Canada Perimeter Institute for Theoretical Physics Waterloo N2L 2Y5 ON Canada

We present a scheme to describe the dynamics of accelerating discrete-time quantum walk for one-and two-particle in position space. We show the effect of acceleration in enhancing the entanglement between the particle and position space in one-particle quantum walk and in generation of entanglement between the two unentangled particle in two-particle quantum walk. By introducing the disorder in the form of phase operator we study the transition from localization to delocalization as a function of acceleration. These inter-winding connection between acceleration, entanglement generation and localization along with well established connection of quantum walks with Dirac equation can be used to probe further in the direction of understanding the connection between acceleration, mass and entanglement in relativistic quantum mechanics and quantum field theory. Expansion of operational tools for quantum simulations and for modelling quantum dynamics of accelerated particle using quantum walks is an other direction where these results can play an important role. © 2019 The Author(s). Published by IOP Publishing Ltd.

关键词： Acceleration Entanglement Localization Quantum walk

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Concerted alterations of functional connectivity and WM integrity in relationship to early amyloid deposition

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Alzheimer's & Dementia 2022年第S1期18卷

作者： Luigi Lorenzini Beatrice Orso David Vállez García Giuseppe Pontillo Silvia Ingala Sven Haller Kaj Blennow Giovanni B Frisoni Gael Chetelat Pierre Payoux Pablo Martinez-Lage Michael Ewers Adam Waldman Craig W. Ritchie Juan Domingo Gispert Pieter Jelle Visser Henri JMM Mutsaerts Betty M. Tijms Alle Meije Wink Frederik Barkhof Department of Radiology and Nuclear Medicine Amsterdam Neuroscience Vrije Universiteit Amsterdam Amsterdam UMC Amsterdam Netherlands Department of Radiology and Nuclear Medicine Amsterdam UMC Location VuMC Vijre Universiteit Amsterdam Amsterdam Netherlands Department of Neuroscience Rehabilitation Ophthalmology Genetics Maternal and Child Health (DINOGMI) University of Genoa Genova Italy Department of Radiology & Nuclear Medicine Amsterdam UMC location VUmc Amsterdam Netherlands Department of Advanced Biomedical Sciences University “Federico II” Naples Italy Department of Electrical Engineering and Information Technology University of Naples “Federico II” Naples Italy University of Geneva Faculty of Medicine Geneva Switzerland Uppsala University Uppsala Sweden Department of Psychiatry and Neurochemistry The Sahlgrenska Academy at the University of Gothenburg Mölndal Sweden Clinical Neurochemistry Laboratory Sahlgrenska University Hospital Mölndal Sweden IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli Brescia Italy Geneva Memory Center Department of Rehabilitation and Geriatrics Geneva University Hospitals Geneva Switzerland ToNIC Toulouse NeuroImaging Center Université de Toulouse Inserm UPS Toulouse France INSERM Imagerie cérébrale et handicaps neurologiques Toulouse France CITA-Alzheimer Foundation San Sebastian Spain German Center for Neurodegenerative Diseases (DZNE) Munich Germany Imperial College London London United Kingdom Centre for Clinical Brain Sciences The University of Edinburgh Edinburgh United Kingdom Centre for Dementia Prevention at the University of Edinburgh Edinburgh United Kingdom Centro de Investigación Biomédica en Red Bioingeniería Biomateriales y Nanomedicina Madrid Spain Barcelonaβeta Brain Research Center (BBRC) Pasqual Maragall Foundation Barcelona Spain IMIM (Hospital del Mar Medical Research Institute) Barcelona Spain Universitat Pompeu Fabra Barcelona Spain Alzheimer Centrum Limburg Maastricht Univ

Background Early amyloid deposition results in functional and structural brain alterations in predementia stages of Alzheimer's disease (AD). However, how early functional and structural brain changes are related to each other remains unclear. Investigating the simultaneous disruptions of functional-structural brain features within individuals in relation to amyloid deposition may increase our understanding of the neuropathological processes underlying AD. Method We included 648 non-demented participants from the European Prevention for Alzheimer’s Dementia (EPAD) cohort vIMI baseline data release. The cut-off for cerebrospinal fluid (CSF) amyloid-β positivity (A+) was defined at <1000pg/mL (Elecsys assay). Functional connectivity was estimated with functional eigenvector centrality (EC) from the resting state functional MRI. White matter (WM) integrity was estimated with fractional anisotropy (FA), computed on diffusion MRI. Both measures were computed at the voxel level within the gray and white matter, respectively. First, we used linear regression models to investigate differences between A+ and A- participants within each modality separately, adjusting for age, sex, and site. In the whole group, we performed sparse canonical correlation analysis (sCCA) on functional and structural measures, identifying shared components between the two modalities. Individual sCCA scores were compared between amyloid groups using a generalized linear model (GLM). To evaluate this association in A+ individuals, the same sCCA analysis was performed normalizing the structural and functional matrices using the mean and SD from A- participants. Results Sample characteristics are provided in Table 1 . Differences in voxelwise EC and FA between amyloid groups are shown in Figure 1 . In the whole group, sCCA analysis showed that EC in the default mode, executive and cerebellar networks covary with FA in parietal, temporal and cerebellar areas ( Figure 2 ). sCCA projections were differen

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