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Training Optimization for Gate-Model Quantum Neural networks

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arXiv 2019年

作者： Gyongyosi, Laszlo Imre, Sandor School of Electronics and Computer Science University of Southampton SouthamptonSO17 1BJ United Kingdom Department of Networked Systems and Services Budapest University of Technology and Economics Budapest1117 Hungary MTA-BME Information Systems Research Group Hungarian Academy of Sciences Budapest1051 Hungary Department of Networked Systems and Services Budapest University of Technology and Economics Budapest1117 Hungary

Gate-based quantum computations represent an essential to realize near-term quantum computer architectures. A gate-model quantum neural network (QNN) is a QNN implemented on a gate-model quantum computer, realized via a set of unitaries with associated gate parameters. Here, we define a training optimization procedure for gate-model QNNs. By deriving the environmental attributes of the gate-model quantum network, we prove the constraint-based learning models. We show that the optimal learning procedures are different if side information is available in different directions, and if side information is accessible about the previous running sequences of the gate-model QNN. The results are particularly convenient for gate-model quantum computer implementations. Copyright © 2019, The Authors. All rights reserved.

关键词： computer architecture

Opportunistic entanglement distribution for the quantum internet

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arXiv 2019年

Quantum entanglement is a building block of the entangled quantum networks of the quantum Internet. A fundamental problem of the quantum Internet is entanglement distribution. Since quantum entanglement will be fundamental to any future quantum networking scenarios, the distribution mechanism of quantum entanglement is a critical and emerging issue in quantum networks. Here we define the method of opportunistic entanglement distribution for the quantum Internet. The opportunistic model defines distribution sets that are aimed to select those quantum nodes for which the cost function picks up a local minimum. The cost function utilizes the error patterns of the local quantum memories and the predictability of the evolution of the entanglement fidelities. Our method provides efficient entanglement distributing with respect to the actual statuses of the local quantum memories of the node pairs. The model provides an easily-applicable, moderate-complexity solution for high-fidelity entanglement distribution in experimental quantum Internet scenarios. Copyright © 2019, The Authors. All rights reserved.

关键词： Quantum entanglement

Neural signatures of motor skill in the resting brain

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arXiv 2019年

作者： Özdenizci, Ozan Meyer, Timm Wichmann, Felix Peters, Jan Schölkopf, Bernhard Çetin, Müjdat Grosse-Wentrup, Moritz Department of Electrical and Computer Engineering Northeastern University BostonMA United States Signal Processing and Information Systems Laboratory Faculty of Engineering and Natural Sciences Sabancı University Istanbul Turkey Max Planck Institute for Intelligent Systems Tübingen Germany Faculty of Science University of Tübingen Bernstein Center for Computational Neuroscience Tübingen Tübingen Germany FG Intelligente Autonome Systeme Technische Universität Darmstadt Darmstadt Germany Department of Electrical and Computer Engineering University of Rochester RochesterNY United States Research Group Neuroinformatics Faculty of Computer Science University of Vienna Vienna Austria

Stroke-induced disturbances of large-scale cortical networks are known to be associated with the extent of motor deficits. We argue that identifying brain networks representative of motor behavior in the resting brain would provide significant insights for current neurorehabilitation approaches. Particularly, we aim to investigate the global configuration of brain rhythms and their relation to motor skill, instead of learning performance as broadly studied. We empirically approach this problem by conducting a three-dimensional physical space visuomotor learning experiment during electroencephalographic (EEG) data recordings with thirty-seven healthy participants. We demonstrate that across-subjects variations in average movement smoothness as the quantified measure of subjects' motor skills can be predicted from the global configuration of resting-state EEG alpha-rhythms (8-14 Hz) recorded prior to the experiment. Importantly, this neural signature of motor skill was found to be orthogonal to (independent of) task- as well as to learning-related changes in alpha-rhythms, which we interpret as an organizing principle of the brain. We argue that disturbances of such configurations in the brain may contribute to motor deficits in stroke, and that reconfiguring stroke patients' brain rhythms by neurofeedback may enhance post-stroke neurorehabilitation. Copyright © 2019, The Authors. All rights reserved.

关键词： Electroencephalography

Checkpointing distributed application running on mobile ad hoc networks

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International Journal of High Performance Computing and Networking 2018年第2期11卷 95-107页

作者： Mansouri, Houssem Badache, Nadjib Aliouat, Makhlouf Pathan, Al-Sakib Khan Department of Computer Science Faculty of Exact Sciences University of Bejaia Bejaia06000 Algeria Research Center on Scientific and Technical Information CERIST Ben-Aknoun Algiers16000 Algeria Laboratory of Networks and Distributed Systems Computer Science Department University of Ferhat Abbas Stif1 Stif19000 Algeria Faculty of Computer and Information Systems Islamic University in Madinah Madinah al-Munawwarah Saudi Arabia CSE Department University of Asia Pacific Bangladesh

Mobile ad hoc network (MANET) is a type of wireless network consisting of a set of self-configured mobile hosts that can communicate with each other using wireless links without the assistance of any fixed infrastructure. This has made it possible for us to create distributed mobile computing applications and has also brought several new challenges in the field of distributed algorithm design. Checkpointing is a well explored fault tolerance technique for the wired and cellular mobile networks. However, it is not directly applicable to MANET owing to its dynamic topology, limited availability of stable storage, partitioning and the absence of fixed infrastructure. In this paper, we propose an adaptive, coordinated and non-blocking checkpointing algorithm to provide fault tolerance in cluster-based MANET, where only a minimum number of mobile hosts in the cluster should take checkpoints. The performance analysis and simulation results show that the proposed scheme requires less coordinating-message cost and performs well compared to the related previous works. Copyright ? 2018 Inderscience Enterprises Ltd.

关键词： Fault tolerance

Ten quick tips for deep learning in biology

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arXiv 2021年

作者： Lee, Benjamin D. Gitter, Anthony Greene, Casey S. Raschka, Sebastian Maguire, Finlay Titus, Alexander J. Kessler, Michael D. Lee, Alexandra J. Chevrette, Marc G. Stewart, Paul Allen Britto-Borges, Thiago Cofer, Evan M. Yu, Kun-Hsing Carmona, Juan Jose Fertig, Elana J. Kalinin, Alexandr A. Signal, Beth Lengerich, Benjamin J. Triche, Timothy J. Boca, Simina M. In-Q-Tel Labs School of Engineering and Applied Sciences Harvard University Department of Genetics Harvard Medical School United States Department of Biostatistics and Medical Informatics University of Wisconsin-Madison MadisonWI United States Morgridge Institute for Research MadisonWI United States Department of Systems Pharmacology and Translational Therapeutics Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Biochemistry and Molecular Genetics University of Colorado School of Medicine AuroraCO United States Center for Health AI University of Colorado School of Medicine AuroraCO United States Department of Statistics University of Wisconsin Madison United States Faculty of Computer Science Dalhousie University Canada University of New Hampshire Bioeconomy.XYZ United States Department of Oncology Johns Hopkins University United States Institute for Genome Sciences University of Maryland School of Medicine United States Genomics and Computational Biology Graduate Program University of Pennsylvania United States Department of Systems Pharmacology and Translational Therapeutics University of Pennsylvania United States Wisconsin Institute for Discovery Department of Plant Pathology University of Wisconsin-Madison United States Department of Biostatistics and Bioinformatics Moffitt Cancer Center TampaFL United States Section of Bioinformatics and Systems Cardiology Klaus Tschira Institute for Integrative Computational Cardiology University Hospital Heidelberg Germany University Hospital Heidelberg Germany Lewis-Sigler Institute for Integrative Genomics Princeton University PrincetonNJ United States Graduate Program in Quantitative and Computational Biology Princeton University PrincetonNJ United States Department of Biomedical Informatics Harvard Medical School United States Department of Pathology Brigham and Women's Hospital United States Philips Healthcare CambridgeMA United States Philips Research

Machine learning is a modern approach to problem-solving and task automation. In particular, machine learning is concerned with the development and applications of algorithms that can recognize patterns in data and use them for predictive modeling. Artificial neural networks are a particular class of machine learning algorithms and models that evolved into what is now described as deep learning. Given the computational advances made in the last decade, deep learning can now be applied to massive data sets and in innumerable contexts. Therefore, deep learning has become its own subfield of machine learning. In the context of biological research, it has been increasingly used to derive novel insights from high-dimensional biological data. To make the biological applications of deep learning more accessible to scientists who have some experience with machine learning, we solicited input from a community of researchers with varied biological and deep learning interests. These individuals collaboratively contributed to this manuscript's writing using the GitHub version control platform and the Manubot manuscript generation toolset. The goal was to articulate a practical, accessible, and concise set of guidelines and suggestions to follow when using deep learning. In the course of our discussions, several themes became clear: the importance of understanding and applying machine learning fundamentals as a baseline for utilizing deep learning, the necessity for extensive model comparisons with careful evaluation, and the need for critical thought in interpreting results generated by deep learning, among others. © 2021, CC BY.

关键词： Learning algorithms

Entrans: Leveraging kinetic energy harvesting signal for transportation mode detection

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arXiv 2018年

作者： Lany, Guohao Xu, Weitao Ma, Dong Khalifa, Sara Hassan, Mahbub Hu, Wen Department of Electrical and Computer Engineering Duke University DurhamNC27708 United States College of Computer Science and Software Engineering Shenzhen University China School of Computer Science and Engineering University of New South Wales Sydney Australia Distributed Sensing Systems research group Data61 CSIRO Australia

Monitoring the daily transportation modes of an individual provides useful information in many application domains, such as urban design, real-time journey recommendation, as well as providing location-based services. In existing systems, accelerometer and GPS are the dominantly used signal sources for transportation context monitoring which drain out the limited battery life of the wearable devices very quickly. To resolve the high energy consumption issue, in this paper, we present EnTrans, which enables transportation mode detection by using only the kinetic energy harvester as an energy-efficient signal source. The proposed idea is based on the intuition that the vibrations experienced by the passenger during traveling with different transportation modes are distinctive. Thus, voltage signal generated by the energy harvesting devices should contain sufficient features to distinguish different transportation modes. We evaluate our system using over 28 hours of data, which is collected by eight individuals using a practical energy harvesting prototype. The evaluation results demonstrate that EnTrans is able to achieve an overall accuracy over 92% in classifying five different modes while saving more than 34% of the system power compared to conventional accelerometer-based approaches. Copyright © 2018, The Authors. All rights reserved.

关键词： Accelerometers

Lack of effects of four-week theta burst stimulation on white matter macro/microstructure in children and adolescents with autism

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NeuroImage. Clinical 2023年 37卷 103324页

作者： Hsing-Chang Ni Yi-Ping Chao Rung-Yu Tseng Chen-Te Wu Luca Cocchi Tai-Li Chou Rou-Shayn Chen Susan Shur-Fen Gau Chun-Hung Yeh Hsiang-Yuan Lin Department of Psychiatry Chang Gung Memorial Hospital at Linkou Taoyuan Taiwan. Deparment of Computer Science and Information Engineering Chang Gung University Taoyuan Taiwan Department of Otorhinolaryngology-Head and Neck Surgery Chang Gung Memorial Hospital at Linkou Taoyuan Taiwan. Department of Psychiatry Chang Gung Memorial Hospital at Linkou Taoyuan Taiwan Institute for Radiological Research Chang Gung University Taoyuan Taiwan. Department of Medical Imaging and Intervention Chang Gung Memorial Hospital at Linkou Taoyuan Taiwan. Clinical Brain Networks Group QIMR Berghofer Medical Research Institute Brisbane Queensland Australia. Department of Psychology National Taiwan University Taipei Taiwan Graduate Institute of Brain and Mind Sciences College of Medicine National Taiwan University Taipei Taiwan Neurobiology and Cognitive Science Center National Taiwan University Taipei Taiwan. Department of Neurology Chang Gung Memorial Hospital at Linkou Taoyuan Taiwan. Department of Psychiatry National Taiwan University Hospital and College of Medicine Taipei Taiwan. Institute for Radiological Research Chang Gung University Taoyuan Taiwan. Electronic address: chunhung.yeh@mail.cgu.edu.tw. Azrieli Adult Neurodevelopmental Centre Campbell Family Mental Health Research Institute Centre for Addiction and Mental Health Toronto Ontario Canada Department of Psychiatry Temerty Faculty of Medicine University of Toronto Toronto Ontario Canada.

Following the published behavioral and cognitive results of this single-blind parallel sham-controlled randomized clinical trial, the current study aimed to explore the impact of intermittent theta burst stimulation (iTBS), a variant of excitatory transcranial magnetic stimulation, over the bilateral posterior superior temporal sulci (pSTS) on white matter macro/microstructure in intellectually able children and adolescents with autism. Participants were randomized and blindly received active or sham iTBS for 4 weeks (the single-blind sham-controlled phase). Then, all participants continued to receive active iTBS for another 4 weeks (the open-label phase). The clinical results were published elsewhere. Here, we present diffusion magnetic resonance imaging data on potential changes in white matter measures after iTBS. Twenty-two participants in Active-Active group and 27 participants in Sham-Active group underwent multi-shell high angular resolution diffusion imaging (64-direction for b = 2000 & 1000 s/mm, respectively) at baseline, week 4, and week 8. With longitudinal fixel-based analysis, we found no white matter changes following iTBS from baseline to week 4 (a null treatment by time interaction and a null within-group paired comparison in the Active-Active group), nor from baseline to week 8 (null within-group paired comparisons in both Active-Active and Sham-Active groups). As for the brain-symptoms relationship, we did not find baseline white matter metrics associated with symptom changes at week 4 in either group. Our results raise the question of what the minimal cumulative stimulation dose required to induce the white matter plasticity is.

关键词： Autism Diffusion MRI Posterior superior temporal sulcus Randomized controlled trial Theta burst stimulation Transcranial magnetic stimulation

Energetic electron precipitation driven by electromagnetic ion cyclotron waves from ELFIN’s low altitude perspective

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arXiv 2022年

作者： Angelopoulos, V. Zhang, X.-J. Artemyev, A.V. Mourenas, D. Tsai, E. Wilkins, C. Runov, A. Liu, J. Turner, D.L. Li, W. Khurana, K. Wirz, R.E. Sergeev, V.A. Meng, X. Wu, J. Hartinger, M.D. Raita, T. Shen, Y. An, X. Shi, X. Bashir, M.F. Shen, X. Gan, L. Qin, M. Capannolo, L. Ma, Q. Russell, C.L. Masongsong, E.V. Caron, R. He, I. Iglesias, L. Jha, S. King, J. Kumar, S. Le, K. Mao, J. McDermott, A. Nguyen, K. Norris, A. Palla, A. Roosnovo Tam, J. Xie, E. Yap, R.C. Ye, S. Young, C. Adair, L.A. Shaffer, C. Chung, M. Cruce, P. Lawson, M. Leneman, D. Allen, M. Anderson, M. Arreola-Zamora, M. Artinger, J. Asher, J. Branchevsky, D. Cliffe, M. Colton, K. Costello, C. Depe, D. Domae, B.W. Eldin, S. Fitzgibbon, L. Flemming, A. Frederick, D.M. Gilbert, A. Hesford, B. Krieger, R. Lian, K. McKinney, E. Miller, J.P. Pedersen, C. Qu, Z. Rozario, R. Rubly, M. Seaton, R. Subramanian, A. Sundin, S.R. Tan, A. Thomlinson, D. Turner, W. Wing, G. Wong, C. Zarifian, A. Earth Planetary and Space Sciences Department Institute of Geophysics and Planetary Physics University of California Los Angeles Los AngelesCA90095 United States University of Texas at Dallas RichardsonTX75080 United States CEA DAM DIF Arpajon France Atmospheric and Oceanic Sciences Departments University of California Los AngelesCA United States Johns Hopkins University Applied Physics Laboratory LaurelMD United States Department of Astronomy Center for Space Physics Boston University BostonMA United States Mechanical and Aerospace Engineering Department Henry Samueli School of Engineering University of California Los AngelesCA90095 United States School of Mechanical Industrial Manufacturing Engineering Oregon State University CorvallisOR97331 United States University of St. Petersburg St. Petersburg Russia Jet Propulsion Laboratory California Institute of Technology PasadenaCA91109 United States Space Science Institute BoulderCO80301 United States Sodankylä Geophysical Observatory University of Oulu Sodankylä Finland Materials Science and Engineering Department Henry Samueli School of Engineering University of California Los AngelesCA90095 United States Deloitte Consulting New YorkNY10112 United States Computer Science Department Henry Samueli School of Engineering University of California Los AngelesCA90095 United States Microsoft RedmondWA98052 United States Physics and Astronomy Department University of California Los AngelesCA90095 United States Department of Astronomy and Astrophysics The University of Chicago ChicagoIL60637 United States Raybeam Inc. Mountain ViewCA94041 United States SpaceX HawthorneCA90250 United States Reliable Robotics Corporation Mountain ViewCA94043 United States Los Alamos National Laboratory Los AlamosNM87545 United States Mathematics Department University of California Los AngelesCA90095 United States Planet Labs PBC San FranciscoCA94107 United States KSAT Inc. De

We review comprehensive observations of electromagnetic ion cyclotron (EMIC) wave-driven energetic electron precipitation using data from the energetic electron detector on the Electron Losses and Fields InvestigatioN (ELFIN) mission, two polar-orbiting low-altitude spinning CubeSats, measuring 50-5000 keV electrons with good pitch-angle and energy resolution. EMIC wave-driven precipitation exhibits a distinct signature in energy-spectrograms of the precipitating-to-trapped flux ratio: peaks at >0.5 MeV which are abrupt (bursty) (lasting ∼17s, or ∆L ∼ 0.56) with significant substructure (occasionally down to sub-second timescale). We attribute the bursty nature of the precipitation to the spatial extent and structuredness of the wave field at the equator. Multiple ELFIN passes over the same MLT sector allow us to study the spatial and temporal evolution of the EMIC wave - electron interaction region. Case studies employing conjugate ground-based or equatorial observations of the EMIC waves reveal that the energy of moderate and strong precipitation at ELFIN approximately agrees with theoretical expectations for cyclotron resonant interactions in a cold plasma. Using 2 years of ELFIN data uniformly distributed in local time, we assemble a statistical database of ∼50 events of strong EMIC wave-driven precipitation. Most reside at L ∼ 5 − 7 at dusk, while a smaller subset exists at L ∼ 8 − 12 at post-midnight. The energies of the peak-precipitation ratio and of the half-peak precipitation ratio (our proxy for the minimum resonance energy) exhibit an L-shell dependence in good agreement with theoretical estimates based on prior statistical observations of EMIC wave power spectra. The precipitation ratio’s spectral shape for the most intense events has an exponential falloff away from the peak (i.e., on either side of ∼ 1.45 MeV). It too agrees well with quasi-linear diffusion theory based on prior statistics of wave spectra. It should be noted though that this diffusive

关键词： Radiation belts

A review of PROFIBUS protocol vulnerabilities: Considerations for implementing authentication and authorization controls 14

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A review of PROFIBUS protocol vulnerabilities: Consideration...

14th International Joint Conference on e-Business and Telecommunications, ICETE 2017

作者： Watson, Venesa Lou, Xinxin Gao, Yuan AREVA GmbH Erlangen Germany Faculty of Science and Engineering University of Siegen Siegen Germany Department of Computer Networks and Distributed Systems Bielefeld University Bielefeld Germany Department of Computer Science Otto-von-Guericke University Magdeburg Germany

ISBN: (纸本)9789897582592

PROFIBUS is a standard for fieldbus communication, used in industrial networks to support real-time command and control. Similar to network protocols developed then, availability is the security objective prioritized in the PROFIBUS design. Confidentiality and integrity were of lesser importance, as industrial protocols were not intended for public access. However, the publicized weaknesses in industrial technologies, including the inclusion of publicly available technology and protocols in industrial networks, presents major risks to industrial networks. This paper investigates the security risks of and provides suggested security solutions for PROFIBUS. The objective is to review the PROFIBUS protocol, to establish the purposefulness of the design and its suitability for the applications where it forms a core part of the infrastructure. The security risks of this protocol are then assessed from successful and possible attacks, based on the vulnerabilities. Proposed security solutions are reviewed and additional recommendations made concerning the use of OPC UA, accompanied by an analysis of the cost of these solutions to the efficiency and safety of the PROFIBUS. The findings of this paper indicate that a defense-in-depth approach is more feasible security solution, with strong security controls being implemented at networks interconnecting with the PROFIBUS networks. Copyright © 2017 by SCITEPRESS - science and Technology Publications, Lda. All rights reserved.

关键词： Authentication