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2022 Review of Data-Driven Plasma science

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arXiv 2022年

作者： Anirudh, Rushil Archibald, Rick Asif, M. Salman Becker, Markus M. Benkadda, Sadruddin Bremer, Peer-Timo Budé, Rick H.S. Chang, C.S. Chen, Lei Churchill, R.M. Citrin, Jonathan Gaffney, Jim A. Gainaru, Ana Gekelman, Walter Gibbs, Tom Hamaguchi, Satoshi Hill, Christian Humbird, Kelli Jalas, Sören Kawaguchi, Satoru Kim, Gon-Ho Kirchen, Manuel Klasky, Scott Kline, John L. Krushelnick, Karl Kustowski, Bogdan Lapenta, Giovanni Li, Wenting Ma, Tammy Mason, Nigel J. Mesbah, Ali Michoski, Craig Munson, Todd Murakami, Izumi Najm, Habib N. Erik J. Olofsson, K. Park, Seolhye Peterson, J. Luc Probst, Michael Pugmire, David Sammuli, Brian Sawlani, Kapil Scheinker, Alexander Schissel, David P. Shalloo, Rob J. Shinagawa, Jun Seong, Jaegu Spears, Brian K. Tennyson, Jonathan Thiagarajan, Jayaraman Ticoş, Catalin M. Trieschmann, Jan van Dijk, Jan Van Essen, Brian Ventzek, Peter Wang, Haimin Wang, Jason T.L. Wang, Zhehui Wende, Kristian Xu, Xueqiao Yamada, Hiroshi Yokoyama, Tatsuya Zhang, Xinhua Lawrence Livermore National Laboratory LivermoreCA94550 United States Oak Ridge National Laboratory Oak RidgeTN37830 United States University of California Riverside RiversideCA92521 United States Felix-Hausdorff-Str. 2 Greifswald17489 Germany Aix Marseille University CNRS PIIM UMR 7345 Marseille France Department of Applied Physics Eindhoven University of Technology Netherlands Princeton Plasma Physics Laboratory Princeton NJ08540 United States Institute of Ion Physics and Applied Physics University of Innsbruck Technikerstrasse 25 Innsbruck6020 Austria DIFFER - Dutch Institute for Fundamental Energy Research Eindhoven Netherlands Science and Technology of Nuclear Fusion Group Eindhoven University of Technology Eindhoven Netherlands Department of Physics and Astronomy University of California Los AngelesCA90095 United States NVIDIA 2788 San Tomas Expressway Santa ClaraCA95051 United States Center for Atomic and Molecular Technologies Graduate School of Engineering Osaka University 2-1 Yamadaoka Suita Osaka Japan Department of Nuclear Sciences and Applications International Atomic Energy Agency Wagramer Strasse 5 PO Box 100 Vienna1400 Austria Center for Free-Electron Laser Science Department of Physics Universität Hamburg Luruper Chaussee 149 Hamburg22761 Germany Division of Information and Electronic Engineering Graduate School of Engineering Muroran Institute of Technology Hokkaido Muroran050-8585 Japan Seoul National University Seoul151-741 Korea Republic of Deutsches Elektronen-Synchrotron DESY Notkestr. 85 Hamburg22607 Germany Los Alamos National Laboratory Los AlamosNM87545 United States Center for Ultrafast Optical Science University of Michigan Ann ArborMI48109-2099 United States Department of Mathematics KULeuven University of Leuven Belgium Department of Physical Sciences The University of Kent CanterburyCT2 7NH United Kingdom Department of Chemical and Biomolecular Engineering University of California Berk

Data science and technology offer transformative tools and methods to science. This review article highlights latest development and progress in the interdisciplinary field of data-driven plasma science (DDPS). A large amount of data and machine learning algorithms go hand in hand. Most plasma data, whether experimental, observational or computational, are generated or collected by machines today. It is now becoming impractical for humans to analyze all the data manually. Therefore, it is imperative to train machines to analyze and interpret (eventually) such data as intelligently as humans but far more efficiently in quantity. Despite the recent impressive progress in applications of data science to plasma science and technology, the emerging field of DDPS is still in its infancy. Fueled by some of the most challenging problems such as fusion energy, plasma-processing of materials, and fundamental understanding of the universe through observable plasma phenomena, it is expected that DDPS continues to benefit significantly from the interdisciplinary marriage between plasma science and data science into the foreseeable future. Copyright © 2022, The Authors. All rights reserved.

关键词： Machine learning

Co-whitening of i-vectors for short and long duration speaker verification 19

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Co-whitening of i-vectors for short and long duration speake...

19th Annual Conference of the International Speech Communication, INTERSPEECH 2018

作者： Xu, Longting Lee, Kong Aik Li, Haizhou Yang, Zhen Department of Electrical and Computer Engineering National University of Singapore Singapore Data Science Research Laboratories NEC Corporation Japan Broadband Wireless Communication and Sensor Network Technology Key Lab Nanjing University of Posts and Telecommunications China

An i-vector is a fixed-length and low-rank representation of a speech utterance. It has been used extensively in text-independent speaker verification. Ideally, speech utterances from the same speaker would map to an unique i-vector. However, this is not the case due to some intrinsic and extrinsic factors like physical condition of the speaker, channel difference, noise and notably the duration of speech utterances. In particular, we found that i-vectors extracted from short utterances exhibit larger variance than that of long utterances. To address the problem, we propose a co-whitening approach, taking into account the duration, while maximizing the correlation between the i-vectors of short and long duration. The proposed co-whitening method was derived based on canonical correlation analysis (CCA). Experimental results on NIST SRE 2010 show that co-whitening method is effective in compensating the duration mismatch, leading to a reduction of up to 13.07% in equal error rate (EER). © 2018 International Speech Communication Association. All rights reserved.

关键词： Vectors

Development of System for Simultaneously Present Multiple Videos That Enables Search by Absolute Time

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Journal of electrical engineering 2018年第1期6卷 33-39页

作者： Kazuhiro OTSUKI Yoshihiro FUJITA NHK Science & Technology Research Laboratories Tokyo 157-8510 Japan The Department of Electrical and Electronic Engineering and Computer Science Ehime University Ehime 790-8577 Japan

We propose a system for simultaneously presenting numerous pieces of video content with absolute time metadata attached for effectively utilizing increasing number of pieces of video content. The proposed stored format used for the system is based on the MMT （MPEG （moving picture experts group） media transport） standardized method, which makes it possible to search by absolute time, and it is a format easy to access by HTTP. We implemented software that can simultaneously present multiple video files according to that format. The constructed system was able to provide service within a feasible processing time.

关键词： MMT search by absolute time system for simultaneously present multiple videos.

The association for the advancement of artificial intelligence 2020 workshop program

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The association for the advancement of artificial intelligen...

作者： Bang, Grace Barash, Guy Bea, Ryan Cali, Jacques Castillo-Effen, Mauricio Chen, Xin Cynthia Chhaya, Niyati Dhoopar, Rohan Dumancic, Sebastijan Espinoza, Huáscar Farchi, Eitan Fioretto, Ferdinando Fuentetaja, Raquel Galley, Michel Geib, Christopher Hernández-Orallo, José Huang, Xiaowei Keren, Sarah Kim, Seokhwan Jaidka, Kokil Liu, Xiaomo Lu, Tyler Ma, Zhiqiang Mallah, Richard McDermid, John Michalowski, Martin Mirsky, Reuth Héigeartaigh, Seán Ó. Ramachandran, Deepak Segovia-Aguas, Javier Shaban-Nejad, Arash Shehory, Onn Shwartz, Vered Srivastava, Siddharth Talamadupula, Kartik Tang, Jian Zhang, Dell Zhang, Jian S&P Global. Western Digital University of Southampton United Kingdom Blue Prism Group PLC Lockheed Martin's Advanced Technology Laboratories ArlingtonVA United States University of Hong Kong Hong Kong Adobe Research Google Research Katholieke Universiteit Leuven Belgium Commissariat à ĺÉnergie Atomique France IBM Research Department of Electrical Engineering and Computer Science Syracuse University United States Universidad Carlos III de Madrid Spain Microsoft Research AI SIFT LLC Universitat Politècnica de València Spain Leverhulme Centre for the Future of Intelligence United Kingdom Department of Computer Science University of Liverpool United Kingdom National University of Singapore Singapore Harvard School of Engineering and Applied Sciences in the of Fields of Multiagent Environment Design and Goal Recognition Design Amazon Alexa AI Future of Life Institute United States University of York Assuring Autonomy International Program United Kingdom University of Minnesota School of Nursing MinneapolisMN United States University of Texas at Austin AustinTX United States Institut de Robòtica i Informàtica Industrial Spanish Council for Scientific Research Technical University of Catalonia Spain Oak Ridge National Laboratory Center for Biomedical Informatics Department of Pediatrics University of Tennessee Health Science Center United States Bar Ilan University Israel University of Washington SeattleWA United States Autonomous Agents and Intelligent Robots lab of the School of Computing Informatics Decision Systems Arizona State University United States DiDi AI Labs School of Industrial and System Engineering Georgia Institute of Technology United States University of London United Kingdom Microsoft Azure

The Association for the Advancement of Artificial Intelligence 2020 Workshop Program included twenty-three workshops covering a wide range of topics in artificial intelligence. This report contains the required reports, which were submitted by most, but not all, of the workshop chairs. Copyright © 2020, Association for the Advancement of Artificial Intelligence. All rights reserved.

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Size effect on memristive properties of nanocrystalline ZnO film for resistive synaptic devices

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Size effect on memristive properties of nanocrystalline ZnO ...

5th International School and Conference on Optoelectronics, Photonics, engineering and Nanostructures, Saint Petersburg OPEN 2018

作者： Shandyba, N.A. Panchenko, I.V. Tominov, R.V. Smirnov, V.A. Pelipenko, M.I. Zamburg, E.G. Chu, Y.H. Department of Nanotechnology and Microsystems Southern Federal University Taganrog347928 Russia UAC Company BERIEV Taganrog347923 Russia Department of Electrical and Computer Engineering National University of Singapore Singapore117582 Singapore Department of Materials Science and Engineering National Chiao Tung University Hsinchu1001 Taiwan Department of Electrophysics National Chiao Tung University Hsinchu1001 Taiwan Institute of Physics Academia Sinica Taipei11529 Taiwan Material and Chemical Research Laboratories Industrial Technology Research Institute Hsinchu31040 Taiwan

Size effect on memristive properties of nanocrystalline ZnO film was investigated. It was shown, ZnO film thickness increase from 6.23±1.54 nm to 47.60±8.12 nm leads to high-resistance state (HRS) increase from 3.26±2.14 M to 700.32±300.83 M and low-resistance state (LRS) from 0.03±0.02 M to 0.09±0.03 M, respectively. The HRS/LRS ratio increases from 108 to 7742. The results can be useful for based on nanocrystalline ZnO films resistive synaptic devices manufacturing. © Published under licence by IOP Publishing Ltd.

关键词： II-VI semiconductors

Hidden silicon-vacancy centers in diamond

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arXiv 2020年

作者： Smallwood, Christopher L. Ulbricht, Ronald Day, Matthew W. Schröder, Tim Bates, Kelsey M. Autry, Travis M. Diederich, Geoffrey Bielejec, Edward Siemens, Mark E. Cundiff, Steven T. Department of Physics University of Michigan Ann ArborMI48109 United States Department of Physics and Astronomy San José State University San JoseCA95192 United States Max Planck Institute for Polymer Research Ackermannweg 10 Mainz55128 Germany Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02138 United States Department of Physics Humboldt-Universität zu Berlin Newtonstraße 15 Berlin12489 Germany JILA University of Colorado National Institute of Standards and Technology BoulderCO80309 United States Department of Physics University of Colorado BoulderCO80309 United States Department of Physics and Astronomy University of Denver DenverCO80208 United States Sandia National Laboratories AlbuquerqueNM87185 United States

We characterize a high-density sample of negatively charged silicon-vacancy (SiV−) centers in diamond using collinear optical multidimensional coherent spectroscopy. By comparing the results of complementary signal detection schemes, we identify a hidden population of SiV– centers that is not typically observed in photoluminescence, and which exhibits significant spectral inhomogeneity and extended electronic T2 times. The phenomenon is likely caused by strain, indicating a potential mechanism for controlling electric coherence in color-center-based quantum devices. Copyright © 2020, The Authors. All rights reserved.

关键词： Color centers

Exposure-associated DNA methylation among people exposed to multiple industrial pollutants

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Clinical epigenetics 2024年第1期16卷 111页

作者： Chi-Hsin Sally Chen Tzu-Hsuen Yuan Tzu-Pin Lu Hsin-Ying Lee Yi-Hsuen Chen Liang-Chuan Lai Mong-Hsun Tsai Eric Y Chuang Chang-Chuan Chan Institute of Environmental and Occupational Health Sciences College of Public Health National Taiwan University Taipei Taiwan. Department of Health and Welfare College of City Management University of Taipei Taipei Taiwan. Institute of Epidemiology and Preventive Medicine College of Public Health National Taiwan University Taipei Taiwan. Institute of Health Data Analytics and Statistics College of Public Health National Taiwan University Taipei Taiwan. Graduate Institute of Physiology College of Medicine National Taiwan University Taipei Taiwan. Institute of Biotechnology College of Bio-Resources and Agriculture National Taiwan University Taipei Taiwan. Department of Electrical Engineering College of Electrical Engineering and Computer Science National Taiwan University Taipei Taiwan. chuangey@ntu.edu.tw. Biomedical Technology and Device Research Laboratories Industrial Technology Research Institute Hsinchu Taiwan. chuangey@ntu.edu.tw. Research and Development Center for Medical Devices National Taiwan University Taipei Taiwan. chuangey@ntu.edu.tw. Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei Taiwan. chuangey@ntu.edu.tw. Institute of Environmental and Occupational Health Sciences College of Public Health National Taiwan University Taipei Taiwan. ccchan@ntu.edu.tw.

BACKGROUND:Current research on the epigenetic repercussions of exposure to a combination of pollutants is limited. This study aims to discern DNA methylation probes associated with exposure to multiple pollutants, serving as early effect markers, and single-nucleotide polymorphisms (SNPs) as surrogate indicators for population susceptibility. The investigation involved the analysis of urine exposure biomarkers for 11 heavy metals (vanadium, arsenic, mercury, cadmium, chromium, nickel, lead, manganese, copper, strontium, thallium), polycyclic aromatic hydrocarbon (PAHs) (1-hydroxypyrene), genome-wide DNA methylation sequencing, and SNPs array on all study participants. The data were integrated with metabolomics information and analyzed both at a community level based on proximity to home addresses relative to the complex and at an individual level based on exposure biomarker concentrations. RESULTS:On a community level, 67 exposure-related CpG probes were identified, while 70 CpG probes were associated with urine arsenic concentration, 2 with mercury, and 46 with vanadium on an individual level. These probes were annotated to genes implicated in cancers and chronic kidney disease. Weighted quantile sum regression analysis revealed that vanadium, mercury, and 1-hydroxypyrene contributed the most to cg08238319 hypomethylation. cg08238319 is annotated to the aryl hydrocarbon receptor repressor (AHRR) gene, and AHRR hypomethylation was correlated with an elevated risk of lung cancer. AHRR was further linked to deregulations in phenylalanine metabolism, alanine, aspartate, and glutamate metabolism, along with heightened oxidative stress. Additionally, three SNPs (rs11085020, rs199442, and rs10947050) corresponding to exposure-related CpG probes exhibited significant interaction effects with multiple heavy metals and PAHs exposure, and have been implicated in cancer progression and respiratory diseases. CONCLUSION:Our findings underscore the pivotal role of AHRR methylatio

关键词： DNA methylation Gene-environment interaction Heavy metals PAHs Petrochemical industry SNPs

Magnetic field fingerprinting of integrated circuit activity with a quantum diamond microscope

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arXiv 2020年

作者： Turner, Matthew J. Langellier, Nicholas Bainbridge, Rachel Walters, Dan Meesala, Srujan Babinec, Thomas M. Kehayias, Pauli Yacoby, Amir Hu, Evelyn Lončar, Marko Walsworth, Ronald L. Levine, Edlyn V. Department of Physics Harvard University CambridgeMA02138 United States Center for Brain Science Harvard University CambridgeMA02138 United States Harvard-Smithsonian Center for Astrophysics CambridgeMA02138 United States MITRE Corporation BedfordMA01730 United States John A. Paulson School of Engineering and Applied Sciences Harvard University CambridgeMA02138 United States Sandia National Laboratories AlbuquerqueNM87123 United States Department of Physics University of Maryland College ParkMD20740 United States Department of Computer and Electrical Engineering University of Maryland College ParkMD20740 United States Quantum Technology Center University of Maryland College ParkMD20740 United States

Current density distributions in active integrated circuits (ICs) result in patterns of magnetic fields that contain structural and functional information about the IC. Magnetic fields pass through standard materials used by the semiconductor industry and provide a powerful means to fingerprint IC activity for security and failure analysis applications. Here, we demonstrate high spatial resolution, wide field-of-view, vector magnetic field imaging of static (DC) magnetic field emanations from an IC in different active states using a Quantum Diamond Microscope (QDM). The QDM employs a dense layer of fluorescent nitrogen-vacancy (NV) quantum defects near the surface of a transparent diamond substrate placed on the IC to image magnetic fields. We show that QDM imaging achieves simultaneous ∼ 10 µm resolution of all three vector magnetic field components over the 3.7 mm × 3.7 mm field-of-view of the diamond. We study activity arising from spatially-dependent current flow in both intact and decapsulated field-programmable gate arrays (FPGAs);and find that QDM images can determine pre-programmed IC active states with high fidelity using machine-learning classification methods. Copyright © 2020, The Authors. All rights reserved.

关键词： Timing circuits

Achieving a quantum smart workforce

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arXiv 2020年

作者： Aiello, Clarice D. Awschalom, D.D. Bernien, Hannes Brower-Thomas, Tina Brown, Kenneth R. Brun, Todd A. Caram, Justin R. Chitambar, Eric Di Felice, Rosa Fox, Michael F.J. Haas, Stephan Holleitner, Alexander W. Hudson, Eric R. Hunt, Jeffrey H. Joynt, Robert Koziol, Scott Lewandowski, H.J. McClure, Douglas T. Palsberg, Jens Passante, Gina Pudenz, Kristen L. Richardson, Christopher J.K. Rosenberg, Jessica L. Ross, R.S. Saffman, Mark Singh, M. Steuerman, David W. Stark, Chad Thijssen, Jos Vamivakas, A. Nick Whitfield, James D. Zwickl, Benjamin M. Department of Electrical and Computer Engineering University of California Los Angeles Los AngelesCA90095 United States Pritzker School of Molecular Engineering University of Chicago ChicagoIL60637 United States Department of Physics University of Chicago ChicagoIL60637 United States Center for Molecular Engineering and Materials Science Division Argonne National Laboratory LemontIL60439 United States Howard University Graduate School WashingtonDC20059 United States Center for Integrated Quantum Materials Howard University PI WashingtonDC20059 United States Departments of Electrical and Computer Engineering Chemistry and Physics Duke University DurhamNC27708 United States Department of Electrical and Computer Engineering University of Southern California Los AngelesCA90089 United States UCLA Department of Chemistry and Biochemistry Center for Quantum Science and Engineering University of California – Los Angeles Los AngelesCA90095 United States Department of Electrical and Computer Engineering University of Illinois Urbana-ChampaignIL61801 United States Department of Physics and Astronomy University of Southern California Los AngelesCA90089 United States JILA National Institute of Standards and Technology University of Colorado BoulderCO80309 United States Department of Physics University of Colorado BoulderCO80309 United States Department of Physics and Astronomy University of Southern California Los AngelesCA90089 United States Garching85748 Germany UCLA Center for Quantum Science and Engineering University of California – Los Angeles Los AngelesCA90095 United States Boeing Company El SegundoCA90245 United States Department of Physics University of Wisconsin-Madison MadisonWI53706 United States Department of Electrical and Computer Engineering Baylor University WacoTX76798 United States Department of Physics University of Colorado BoulderCO80309 United States IBM T.J. Watson Research Center Yorktown HeightsNY

Interest in building dedicated Quantum Information science and engineering (QISE) education programs has greatly expanded in recent years. These programs are inherently convergent, complex, often resource intensive and likely require collaboration with a broad variety of stakeholders. In order to address this combination of challenges, we have captured ideas from many members in the community. This manuscript not only addresses policy makers and funding agencies (both public and private and from the regional to the international level) but also contains needs identified by industry leaders and discusses the difficulties inherent in creating an inclusive QISE curriculum. We report on the status of eighteen post-secondary education programs in QISE and provide guidance for building new programs. Lastly, we encourage the development of a comprehensive strategic plan for quantum education and workforce development as a means to make the most of the ongoing substantial investments being made in QISE. Copyright © 2020, The Authors. All rights reserved.

关键词： Personnel