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arXiv 2021年

作者： Lubinski, Thomas Johri, Sonika Varosy, Paul Coleman, Jeremiah Zhao, Luning Necaise, Jason Baldwin, Charles H. Mayer, Karl Proctor, Timothy Quantum Circuits Inc 25 Science Park New HavenCT06511 United States QED-C Technical Advisory Committee on Standards and Performance Benchmarks United States IonQ Inc 4505 Campus Dr College ParkMD20740 United States Department of Physics Colorado School of Mines GoldenCO80401 United States Department of Electrical and Computer Engineering Princeton University PrincetonNJ08544 United States D-Wave Systems BurnabyBCV5G 4M9 Canada Quantinuum 303 S. Technology Ct BroomfieldCO80021 United States Quantum Performance Laboratory Sandia National Laboratories LivermoreCA94550 United States

In this work we introduce an open source suite of quantum application-oriented performance benchmarks that is designed to measure the effectiveness of quantum computing hardware at executing quantum applications. These benchmarks probe a quantum computer's performance on various algorithms and small applications as the problem size is varied, by mapping out the fidelity of the results as a function of circuit width and depth using the framework of volumetric benchmarking. In addition to estimating the fidelity of results generated by quantum execution, the suite is designed to benchmark certain aspects of the execution pipeline in order to provide end-users with a practical measure of both the quality of and the time to solution. Our methodology is constructed to anticipate advances in quantum computing hardware that are likely to emerge in the next five years. This benchmarking suite is designed to be readily accessible to a broad audience of users and provides benchmarks that correspond to many well-known quantum computing algorithms. Copyright © 2021, The Authors. All rights reserved.

关键词： Benchmarking

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STROBE-X Mission Overview

arXiv

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arXiv 2024年

作者： Ray, Paul S. Roming, Peter W.A. Argan, Andrea Arzoumanian, Zaven Ballantyne, David R. Bogdanov, Slavko Bonvicini, Valter Brandt, Terri J. Bursa, Michal Cackett, Edward M. Chakrabarty, Deepto Christophersen, Marc Coderre, Kathleen M. De Geronimo, Gianluigi Del Monte, Ettore DeRosa, Alessandra Dietz, Harley R. Evangelista, Yuri Feroci, Marco Ford, Jeremy J. Froning, Cynthia Fryer, Christopher L. Gendreau, Keith C. Goldstein, Adam Gonzalez, Anthony H. Hartmann, Dieter Hernanz, Margarita Hutcheson, Anthony Zand, Jean in't Jenke, Peter Kennea, Jamie Lloyd-Ronning, Nicole M. Maccarone, Thomas J. Maes, Dominic Markwardt, Craig B. Michalska, Malgorzata Okajima, Takashi Patruno, Alessandro Persyn, Steven C. Phillips, Mark L. Prescod-Weinstein, Chanda Redfern, Jillian A. Remillard, Ronald A. Santangelo, Andrea Schwendeman, Carl L. Sleator, Clio Steiner, James Strohmayer, Tod E. Svoboda, Jiri Tenzer, Christoph Thompson, Steven P. Warwick, Richard W. Watts, Anna L. Wilson-Hodge, Colleen A. Wu, Xin Wulf, Eric A. Zampa, Gianluigi Space Science Division U.S. Naval Research Laboratory WashingtonDC20375 United States Southwest Research Institute San AntonioTX78238 United States NASA’s Goddard Space Flight Center GreenbeltMD20771 United States Columbia Astrophysics Laboratory Columbia University New YorkNY10027 United States Trieste TS Italy SRON Netherlands Institute for Space Research Niels Bohrweg 4 CA Leiden2333 Netherlands Astronomical Institute of the Czech Academy of Sciences Boční II 1401 Prague14100 Czech Republic Department of Physics & Astronomy Wayne State University DetroitMI48201 United States Kavli Institute for Astrophysics and Space Research Massachusetts Institute of Technology CambridgeMA02139 United States Department of Nuclear Engineering and Radiological Sciences Univeristy of Michigan Ann ArborMI United States INAF - Istituto di Astrofisica e Planetologia Spaziali Roma00133 Italy Los Alamos National Laboratory Los AlamosNM87545 United States Universities Space Research Association HuntsvilleAL35805 United States Department of Astronomy University of Florida GainesvilleFL32611 United States IEEC Campus UAB Carrer de Can Magrans s/n Bellaterra Barcelona08193 Spain University of Alabama in Huntsville HuntsvilleAL35805 United States Department of Astronomy and Astrophysics The Pennsylvania State University University ParkPA16802 United States Department of Physics & Astronomy Texas Tech University LubbockTX79409 United States Space Research Center Polish Academy of Sciences Warszawa Poland Department of Physics and Astronomy University of New Hampshire DurhamNH03824 United States Harvard-Smithsonian Center for Astrophysics CambridgeMA02138 United States Eberhard Karls Universität Tübingen Germany Anton Pannekoek Institute for Astronomy University of Amsterdam Amsterdam1090GE Netherlands Astrophysics Branch NASA’s Marshall Space Flight Center HuntsvilleAL35812 United States Department of Nuclear and Particle Physics Univ

We give an overview of the science objectives and mission design of the Spectroscopic Time-Resolving Observatory for Broadband Energy X-rays (STROBE-X) observatory, which has been proposed as a NASA probe-class (∼$1.... 详细信息

关键词： NASA

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Editor-in-Chief

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IEEE Access 2024年 12卷 i-xi页

作者： Derek Abbott Sonia Aissa Anuradha Annaswamy Nirwan Ansari Jun Cai Kun-Shan Chen Yixin Chen J.-C. Chiao Ayman El-Baz Shaikh Fattah Hoay Gooi Maya Gokhale Chih-Lin Ⅰ Giuseppe Iannaccone Yumi Iwashita Bruce Jacob Abbas Jamalipour Bahram Javidi Weihua Jiang Okyay Kaynak Hulya Kirkici Germano Lambert-Torres Shengtao Li Michal Mrozowski Michele Nappi Dalma Novak Hugo Proença Yi Qian Zhihua Qu Susanto Rahardja Mehrdad Saif Ali Serpengüzel Peter H. Siegel Ashitey Trebi-Ollennu Daniela Tuninetti Ge Wang Keith A. Wear Andreas Weisshaar C. Patrick Yue Enrico Zio School of Electrical and Electronic Engineering University of Adelaide Adelaide SA Australia Institut National de la Recherche Scientifique (INRS) Québec City Canada Department of Mechanical Engineering Massachusetts Institute of Technology Cambridge MA USA Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ USA Concordia University Montreal Canada Guilin University of Technology Guilin China Washington University St. Louis MO USA Southern Methodist University Dallas TX USA University of Louisville/Bioengineering Department Louisville KY USA Department of Electrical and Electronic Engineering Bangladesh University of Engineering and Technology Dhaka Bangladesh Nanyang Technological University Jurong West Singapore Lawrence Livermore National Laboratory Livermore CA USA China Mobile Research Institute Beijing China University of Pisa Pisa Italy NASA-JPL California Institute of Technology Pasadena CA USA Florida Polytechnic University Lakeland FL USA The University of Sydney Sydney NSW Australia University of Connecticut Storrs CT USA Nagaoka University of Technology Nagaoka Niigata Japan Department of Electrical and Electronic Engineering Boğaziçi University Istanbul Turkey University of South Alabama Mobile AL USA Gnarus Institute Itajuba Brazil Xi’an Jiaotong University Xi’an China Gdansk University of Technology Gdansk Poland University of Salerno Fisciano Italy Octane Wireless Hanover MD USA University of Beira Interior Covilhã Portugal Department of Electrical and Computer Engineering University of NebraskaLincoln Lincoln NE USA University of Central Florida Orlando Florida USA Singapore Institute of Technology 10 Dover Dr Singapore Infocomm Technology Cluster 10 Dover Dr Singapore University of Windsor Windsor Canada Department of Physics Koç University Istanbul Turkey California Institute of Technology (CalTech) Pasadena California USA NASA-JPL Mobility and Robotics Systems S

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A molecular single-cell lung atlas of lethal COVID-19 (vol 595, pg 114, 2021)

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NATURE 2021年第7882期598卷 E2-E2页

作者： Melms, Johannes C. Biermann, Jana Huang, Huachao Wang, Yiping Nair, Ajay Tagore, Somnath Katsyv, Igor Rendeiro, Andre F. Amin, Amit Dipak Schapiro, Denis Frangieh, Chris J. Luoma, Adrienne M. Filliol, Aveline Fang, Yinshan Ravichandran, Hiranmayi Clausi, Mariano G. Alba, George A. Rogava, Meri Chen, Sean W. Ho, Patricia Montoro, Daniel T. Kornberg, Adam E. Han, Arnold S. Bakhoum, Mathieu F. Anandasabapathy, Niroshana Suarez-Farinas, Mayte Bakhoum, Samuel F. Bram, Yaron Borczuk, Alain Guo, Xinzheng V. Lefkowitch, Jay H. Marboe, Charles Lagana, Stephen M. Del Portillo, Armando Tsai, Emily J. Zorn, Emmanuel Markowitz, Glen S. Schwabe, Robert F. Schwartz, Robert E. Elemento, Olivier Saqi, Anjali Hibshoosh, Hanina Que, Jianwen Izar, Benjamin Department of Medicine Division of Hematology/Oncology Columbia University Irving Medical Center New York NY USA Columbia Center for Translational Immunology Columbia University Irving Medical Center New York NY USA Herbert Irving Comprehensive Cancer Center Columbia University Irving Medical Center New York NY USA Program for Mathematical Genomics Columbia University New York NY USA Columbia Center for Human Development Columbia University Irving Medical Center New York NY USA Division of Digestive and Liver Diseases Columbia University Irving Medical Center New York NY USA Department of Medicine Columbia University Irving Medical Center New York NY USA Institute of Human Nutrition Columbia University New York NY USA Department of Systems Biology Columbia University Irving Medical Center New York NY USA Department of Pathology and Cell Biology Columbia University Irving Medical Center New York NY USA Institute for Computational Biomedicine Weill Cornell Medicine New York NY USA Caryl and Israel Englander Institute for Precision Medicine Weill Cornell Medicine New York NY USA WorldQuant Initiative for Quantitative Prediction Weill Cornell Medicine New York NY USA Department of Physiology and Biophysics Weill Cornell Medical College New York NY USA Department of Dermatology Weill Cornell Medical College New York NY USA Meyer Cancer Center Weill Cornell Medical College New York NY USA Laboratory of Systems Pharmacology Harvard Medical School Boston MA USA Klarman Cell Observatory Broad Institute of MIT and Harvard Cambridge MA USA Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge MA USA Department of Cancer Immunology and Virology Dana-Farber Cancer Center Boston MA USA Human Immune Monitoring Core Columbia University Irving Medical Center New York NY USA Department of Medicine Division of Pulmonary and Critical Care Massachusetts General Hospital Boston MA USA Cell Circu

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Convolutional Neural Networks for Epileptic Seizure Prediction

arXiv

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arXiv 2018年

作者： Eberlein, Matthias Hildebrand, Raphael Tetzlaff, Ronald Hoffmann, Nico Kuhlmann, Levin Brinkmann, Benjamin Müller, Jens Technische Universität Dresden Faculty of Electrical and Computer Engineering Institute of Circuits and Systems Dresden01062 Germany Technische Universität Dresden Faculty of Computer Science Computer Graphics and Visualisation Dresden01062 Germany Faculty of Information Technology Monash University VIC Clayton3800 Australia Department of Medicine St Vincent's Hospital Melbourne VIC Fitzroy3065 Australia Mayo Systems Electrophysiology Laboratory Departments of Neurology and Biomedical Engineering Mayo Clinic RochesterMN55905 United States

Epilepsy is the most common neurological disorder and an accurate forecast of seizures would help to overcome the patient's uncertainty and helplessness. In this contribution, we present and discuss a novel methodology for the classification of intracranial electroencephalography (iEEG) for seizure prediction. Contrary to previous approaches, we categorically refrain from an extraction of hand-crafted features and use a convolutional neural network (CNN) topology instead for both the determination of suitable signal characteristics and the binary classification of preictal and interictal segments. Three different models have been evaluated on public datasets with long-term recordings from four dogs and three patients. Overall, our findings demonstrate the general applicability. In this work we discuss the strengths and limitations of our methodology. Copyright © 2018, The Authors. All rights reserved.

关键词： Electroencephalography

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MoveHN-A database to support the development of motion based biosignal processing systems

MoveHN-A database to support the development of motion based...

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European Signal Processing Conference

作者： Andreas Kitzig Stefan Schroter Edwin Naroska Gudrun Stockmanns Reinhard Viga Anton Grabmaier Faculty of Electrical Engineering and Computer Science Ambient Intelligence Laboratory Krefeld Germany Universitat Duisburg-Essen Duisburg Nordrhein-Westfalen DE Department of Electronic Components and Circuits University of Duisburg-Essen Fraunhofer Institute for Microelectronic Circuits and Systems (IMS) Duisburg Germany

In the field of signal processing, pattern recognition and also modeling and simulation, it is often necessary to use large data sets. These allow reliable, independent and test case spanning development of algorithms or even of complete systems. The data is usually taken from existing data sets such as TIMIT for speech recognition and processing or EPILEPSIAE to develop algorithms for epileptic seizure prediction, to give just two examples. Apart from the fact that some of these databases imply a considerable cost factor and thus are not accessible to all research groups, even greater problems arise if no data is available at all. In the field of speech recognition, this problem was solved more or less by creating databases. In the area of biosignal processing with a focus on the functionalization of furniture for care and clinical facilities, there is still a need for large data sets. This was also the case with biomechanical modeling of functionalized furniture, since up to now none or few data on the human movement sequences were available. In order to overcome this deficiency, the following paper presents a new database of motion patterns, which is intended to support the development of algorithms for motion detection as well as modeling biosignal processing. The database can be used and downloaded by any interested researcher for free.

关键词： Hidden Markov models Mathematical model Biological system modeling Databases Medical services Sensor systems

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Secrecy performance analysis of single-input multiple-output generalized-K fading channels

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Frontiers of Information Technology and Electronic engineering 2016年第10期17卷 1074-1084页

作者： Lei, Hong-jiang Ansari, Imran Shafique Gao, Chao Guo, Yong-cai Pan, Gao-feng Qaraqe, Khalid A. Chongqing Key Laboratory of Mobile Communications Technology Chongqing University of Posts and Telecommunications Chongqing400065 China MOE Key Laboratory of Optoelectronic Technology and Systems Chongqing University Chongqing400044 China Department of Electrical and Computer Engineering Texas A&M University at Qatar Doha Qatar Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Southwest University Chongqing400715 China

In this paper, the transmission of confidential messages through single-input multiple-output (SIMO) independent and identically generalized-K (KG) fading channels is considered, where the eavesdropper overhears the transmission from the transmitter to the receiver. Both the receiver and the eavesdropper are equipped with multiple antennas, and both active and passive eavesdroppings are considered where the channel state information of the eavesdropper’s channel is or is not available at the transmitter. The secrecy performance of SIMO KG systems is investigated. Analytical expressions for secrecy outage probability and average secrecy capacity of SIMO systems are derived via two different methods, in which KG distribution is approximated by the Gamma and mixture Gamma distributions, respectively. Numerical results are presented and verified via the Monte-Carlo simulation. © 2016, Journal of Zhejiang University Science Editorial Office and Springer-Verlag Berlin Heidelberg.

关键词： Fading channels

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Analytical model with lateral force for conventional CMUT membranes under large deflection using Von Kármán equations

Analytical model with lateral force for conventional CMUT me...

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IEEE Symposium (IUS) Ultrasonics

作者： Jiujiang Wang Yuanyu Yu Sio Hang Pun Peng Un Mak U Kin Che Ching-Hsiang Cheng Mang I Vai Department of Electrical and Computer Engineering University of Macau Macau State Key Laboratory of Analog and Mixed-Signal VLSI University of Macau Macau Department of Industrial and Systems Engineering The Hong Kong Polytechnic University Hong Kong

ISBN: (纸本)9781467398985

Capacitive Micromachined Ultrasonic Transducer (CMUT) is a new type of ultrasound wave generator and detector. Analytical method is intuitive to understand the mechanism and physical effects through modeling of CMUT. To optimize the design procedures of CMUT membrane undergoing large deflection, a new analytical model with the consideration of the lateral force using Von Kármán equations is proposed. This model is capable of calculating the membrane profile of the CMUT since it includes the effect of the lateral force. The calculated results match well with the simulated results and the maximum deflection error in the center of the CMUT is less than 1% of the simulation results. The lateral force increases with the deflection of the membrane and it can be found that with the introduction of the lateral force, the proposed model can accurately estimate the membrane large defection profile in both single and double-layer membrane cases. The capacitance of the CMUT can be derived when the deflection profile of the membrane is available.

关键词： Mathematical model Force Electrodes Analytical models Finite element analysis Micromechanical devices Computational modeling

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Optimizing radar waveforms using generalized alternating projections

Optimizing radar waveforms using generalized alternating pro...

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Texas Symposium on Wireless and Microwave circuits and systems, WMCS 2015

作者： Eustice, Dylan Baylis, Charles Latham, Casey Marks, Robert J. Cohen, Lawrence Wireless and Microwave Circuits and Systems Program Department of Electrical and Computer Engineering Baylor University WacoTX United States Radar Division United States Naval Research Laboratory WashingtonDC United States

ISBN: (纸本)9781467380690

The radar ambiguity function, described as an autocorrelation of shifts in time and frequency, is useful for determining a waveform's accuracy at detecting targets in certain range-Doppler combinations. An algorithm is proposed which uses a generalized method of alternating projections to synthesize waveforms with desired ambiguity function properties. In practice, it is often desirable to minimize the magnitude of the ambiguity function at range-Doppler combinations where targets other than the detection are likely to cause interference. The algorithm alternates between projections in the time, frequency, and range-Doppler domains until an optimal solution which fits desired ambiguity function properties is found. This work provides a computationally intelligent methodology to dynamically optimize detection in radar applications and a foundation for future work in joint circuit optimization for spectral compliance. © 2015 IEEE.

关键词： Set theory

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Effects of power amplifier nonlinearities on the radar ambiguity function

Effects of power amplifier nonlinearities on the radar ambig...

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2015 IEEE International Radar Conference, RadarCon 2015

作者： Eustice, Dylan Baylis, Charles Cohen, Lawrence Marks, Robert J. Wireless and Microwave Circuits and Systems Program Department of Electrical and Computer Engineering Baylor University WacoTX United States Radar Division United States Naval Research Laboratory WashingtonDC United States

ISBN: (纸本)9781479982325

The radar ambiguity function describes the possibility of errors in range and Doppler detection for targets of certain range-Doppler combinations. Nonlinear power amplifiers in radar transmitters provide many undesirable effects, including spreading of the radar spectrum. Based on the known impacts of the power amplifier nonlinearities on the waveform and spectrum that is transmitted, this paper assesses the related impacts on the ambiguity function and, therefore, on the estimation precision capabilities of the radar. Simulation results for nonlinear microwave power-amplifier transistor models are presented to illustrate the theory that is presented. Simulations using a Gaussian Barker code implementation show that amplifier nonlinearities cause widening of ambiguity content in the Doppler dimension, widening of range sidelobes, and deepening of range and Doppler nulls. The theory and observations presented in this paper are expected to find significant application in radar waveform optimization to provide desired ambiguity-function properties while maintaining spectral compliance. © 2015 IEEE.

关键词： Power amplifiers

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