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arXiv 2017年

作者： Ouyang, Bin Xiong, Shiyun Yang, Zhi Jing, Yuhang Wang, Yongjie National Center for Supercomputing Applications University of Illinois at Urbana-Champaign UrbanaIL61801 United States Collaborative Innovation Center of Suzhou Nano Science and Technology Soochow University Suzhou JiangSu215123 China College of Physics and Optoelectronics Taiyuan University of Technology Taiyuan ShanXi030024 China Key Lab of Advanced Transducers and Intelligent Control System Ministry of Education and Shanxi Province Taiyuan University of Technology Taiyuan ShanXi030024 China Department of Astronautical Science and Mechanics Harbin Institute of Technology Harbin Heilongjiang150001 China Beckman Institute for Advanced Science and Technology University of Illinois at Urbana-Champaign UrbanaIL61801 United States Department of Electrical Engineering and Computer Engineering University of Michigan Ann ArborMI48109 United States

Due to the distinguished properties offered by different structural phases of monolayer MoS2, phase engineering design are urgently required for achieving switchable structural phase. Strain engineering is widely accepted as a clean and flexible method, however, can not be achieved in engineering monolayer MoS2 phase transition because the critical biaxial strain required (~15%) is much larger than measured elastic limit (~11%). In this study, employing density functional theoretical calculations, it has been found out that with the forming of heterostructure between MoS2 with buckled 2D materials such as silicence, germanene and stanene, only a small strain can trigger the phase transition. As being suggested by the constructed phase stability diagram, biaxial deformation as low as 3% in MoS2/silicene and MoS2/stanene sandwich structure, would be sufficient to induce the structural phase transition in MoS2 lattice. This strain falls well within experimental elastic limit, thus would be feasible to realize in experiment. The origin of such behavior can be understood as strain induced interlayer covalent bond formation, which finally make MoS2 lattice more sensitive to external strain. This theoretical work provides one realistic route for achieving flexible phase stabilities in experimental design. Copyright © 2017, The Authors. All rights reserved.

关键词： Molybdenum compounds

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Author Correction: Open-access quantitative MRI data of the spinal cord and reproducibility across participants, sites and manufacturers

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Scientific data 2021年第1期8卷 242页

作者： Julien Cohen-Adad Eva Alonso-Ortiz Mihael Abramovic Carina Arneitz Nicole Atcheson Laura Barlow Robert L Barry Markus Barth Marco Battiston Christian Büchel Matthew Budde Virginie Callot Anna J E Combes Benjamin De Leener Maxime Descoteaux Paulo Loureiro de Sousa Marek Dostál Julien Doyon Adam Dvorak Falk Eippert Karla R Epperson Kevin S Epperson Patrick Freund Jürgen Finsterbusch Alexandru Foias Michela Fratini Issei Fukunaga Claudia A M Gandini Wheeler-Kingshott Giancarlo Germani Guillaume Gilbert Federico Giove Charley Gros Francesco Grussu Akifumi Hagiwara Pierre-Gilles Henry Tomáš Horák Masaaki Hori James Joers Kouhei Kamiya Haleh Karbasforoushan Miloš Keřkovský Ali Khatibi Joo-Won Kim Nawal Kinany Hagen H Kitzler Shannon Kolind Yazhuo Kong Petr Kudlička Paul Kuntke Nyoman D Kurniawan Slawomir Kusmia René Labounek Maria Marcella Laganà Cornelia Laule Christine S Law Christophe Lenglet Tobias Leutritz Yaou Liu Sara Llufriu Sean Mackey Eloy Martinez-Heras Loan Mattera Igor Nestrasil Kristin P O'Grady Nico Papinutto Daniel Papp Deborah Pareto Todd B Parrish Anna Pichiecchio Ferran Prados Àlex Rovira Marc J Ruitenberg Rebecca S Samson Giovanni Savini Maryam Seif Alan C Seifert Alex K Smith Seth A Smith Zachary A Smith Elisabeth Solana Y Suzuki George Tackley Alexandra Tinnermann Jan Valošek Dimitri Van De Ville Marios C Yiannakas Kenneth A Weber Ii Nikolaus Weiskopf Richard G Wise Patrik O Wyss Junqian Xu NeuroPoly Lab Institute of Biomedical Engineering Polytechnique Montreal Montreal QC Canada. jcohen@polymtl.ca. Functional Neuroimaging Unit CRIUGM Université de Montréal Montreal QC Canada. jcohen@polymtl.ca. Mila - Quebec AI Institute Montreal QC Canada. jcohen@polymtl.ca. NeuroPoly Lab Institute of Biomedical Engineering Polytechnique Montreal Montreal QC Canada. Department of Radiology Swiss Paraplegic Centre Nottwil Switzerland. Centre for Advanced Imaging The University of Queensland Brisbane Australia. Department of Radiology University of British Columbia Vancouver BC Canada. Athinoula A. Martinos Center for Biomedical Imaging Department of Radiology Massachusetts General Hospital Charlestown MA USA. Department of Radiology Harvard Medical School Boston MA USA. Harvard-Massachusetts Institute of Technology Health Sciences & Technology Cambridge MA USA. School of Information Technology and Electrical Engineering The University of Queensland Brisbane Australia. NMR Research Unit Queen Square MS Centre UCL Queen Square Institute of Neurology Faculty of Brain Sciences University College London London UK. Department of Systems Neuroscience University Medical Center Hamburg-Eppendorf Hamburg Germany. Department of Neurosurgery Medical College of Wisconsin Milwaukee WI USA. Aix-Marseille Univ CNRS CRMBM Marseille France. APHM Hopital Universitaire Timone CEMEREM Marseille France. Vanderbilt University Institute of Imaging Science Vanderbilt University Medical Center Nashville TN USA. Department of Computer and Software Engineering Polytechnique Montreal Montreal Canada. CHU Sainte-Justine Research Centre Montreal QC Canada. Centre de Recherche CHUS CIMS Sherbrooke Canada. Sherbrooke Connectivity Imaging Lab (SCIL) Computer Science department Université de Sherbrooke Sherbrooke Canada. Université de Strasbourg CNRS ICube Strasbourg France. UHB - University Hospital Brno and Masaryk University Department of Radiology and Nuclear

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Generating summarized preview for education resource based on exploring and comparing GUIs 28

Generating summarized preview for education resource based o...

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28th International Conference on software engineering and Knowledge engineering, SEKE 2016

作者： Ma, Chao Chen, Xiangping Rao, Yongsheng Lin, Mouguang School of Data and Computer Science Sun Yat-sen University Guangzhou China Research Institute Sun Yat-sen University in Shenzhen Shenzhen China Institute of Advanced Technology Sun Yat-sen University Guangzhou China School of Computer Science and Educational Software Guangzhou University Guangzhou China Institute of Advanced Technology National Engineering Research Center of Digital Life Sun Yat-sen University Guangzhou China

ISBN: (纸本)189170639X

Compared to traditional education resource, Interactive Education Resource (IER) includes dynamic content to interact with users in order to enhance comprehension. The contents of IERs are relatively complex because of its dynamic feature. Exploring IERs and understanding its content during resource search become time-consuming. In this paper, we propose a preview generation approach based on automated software testing and image processing. Our approach first analyzes IERs to collect interactive elements and the event list. Based on the interaction related information, our approach simulates user actions and record snapshots step by step. Our approach compares snapshots to generate an image including the basic content, interaction region and dynamic contents. The image is used as the overall preview and the animation of snapshots collected during simulation is used as detail preview of the IER. In the experiment, we evaluate the completeness, correctness, and comprehension of the preview. The experiment result shows that the preview can be used to provide most information in the resource correctly and easy to understand. Our approach can save time for users in understanding the IERs. Copyright © 2016 by KSI Research Inc. and Knowledge Systems Institute Graduate School.

关键词： Image processing

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Social and moral psychology of COVID-19 across 69 countries

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Scientific data 2023年第1期10卷 272页

作者： Flavio Azevedo Tomislav Pavlović Gabriel G Rêgo F Ceren Ay Biljana Gjoneska Tom W Etienne Robert M Ross Philipp Schönegger Julián C Riaño-Moreno Aleksandra Cichocka Valerio Capraro Luca Cian Chiara Longoni Ho Fai Chan Jay J Van Bavel Hallgeir Sjåstad John B Nezlek Mark Alfano Michele J Gelfand Michèle D Birtel Aleksandra Cislak Patricia L Lockwood Koen Abts Elena Agadullina John Jamir Benzon Aruta Sahba Nomvula Besharati Alexander Bor Becky L Choma Charles David Crabtree William A Cunningham Koustav De Waqas Ejaz Christian T Elbaek Andrej Findor Daniel Flichtentrei Renata Franc June Gruber Estrella Gualda Yusaku Horiuchi Toan Luu Duc Huynh Agustin Ibanez Mostak Ahamed Imran Jacob Israelashvili Katarzyna Jasko Jaroslaw Kantorowicz Elena Kantorowicz-Reznichenko André Krouwel Michael Laakasuo Claus Lamm Caroline Leygue Ming-Jen Lin Mohammad Sabbir Mansoor Antoine Marie Lewend Mayiwar Honorata Mazepus Cillian McHugh John Paul Minda Panagiotis Mitkidis Andreas Olsson Tobias Otterbring Dominic J Packer Anat Perry Michael Bang Petersen Arathy Puthillam Tobias Rothmund Hernando Santamaría-García Petra C Schmid Drozdstoy Stoyanov Shruti Tewari Bojan Todosijević Manos Tsakiris Hans H Tung Radu G Umbres Edmunds Vanags Madalina Vlasceanu Andrew Vonasch Meltem Yucel Yucheng Zhang Mohcine Abad Eli Adler Narin Akrawi Hamza Alaoui Mdarhri Hanane Amara David M Amodio Benedict G Antazo Matthew Apps Mouhamadou Hady Ba Sergio Barbosa Brock Bastian Anton Berg Maria P Bernal-Zárate Michael Bernstein Michał Białek Ennio Bilancini Natalia Bogatyreva Leonardo Boncinelli Jonathan E Booth Sylvie Borau Ondrej Buchel C Daryl Cameron Chrissie F Carvalho Tatiana Celadin Chiara Cerami Hom Nath Chalise Xiaojun Cheng Kate Cockcroft Jane Conway Mateo Andres Córdoba-Delgado Chiara Crespi Marie Crouzevialle Jo Cutler Marzena Cypryańska Justyna Dabrowska Michael A Daniels Victoria H Davis Pamala N Dayley Sylvain Delouvée Ognjan Denkovski Guillaume Dezecache Nathan A Dhaliwal Alelie B Diato Roberto Di Paolo Marianna Drosinou Uwe Dulleck Jānis Ekmanis Department of Psychology University of Cambridge Cambridge England. fa441@cam.ac.uk. Institute of Communication Science Friedrich-Schiller University Jena Jena Germany. fa441@cam.ac.uk. Institute of Social Sciences Ivo Pilar Zagreb Croatia. Social and Cognitive Neuroscience Laboratory Mackenzie Presbyterian University São Paulo Brazil. Department of Economics Norwegian School of Economics Bergen Norway. Telenor Research Oslo Norway. Macedonian Academy of Sciences and Arts Skopje Republic of North Macedonia. Kieskompas - Election Compass Amsterdam Netherlands. Department of Political Science & Annenberg School for Communication University of Pennsylvania Philadelphia PA USA. Department of Psychology Macquarie University Sydney NSW Australia. Department of Philosophy University of St Andrews St Andrews Scotland. School of Economics and Finance University of St Andrews St Andrews Scotland. Medicine Faculty Cooperative University of Colombia Villavicencio Colombia. Department of Bioethics El Bosque University Bogotá Colombia. School of Psychology University of Kent Canterbury England. Department of Economics Middlesex University London London England. Darden School of Business University of Virginia Charlottesville VA USA. Questrom School of Business Boston University Boston MA USA. School of Economics and Finance Queensland University of Technology Brisbane QLD Australia. Center for Behavioural Economics Society and Technology Queensland University of Technology Brisbane QLD Australia. Department of Psychology and Neural Science New York University New York NY USA. Department of Strategy and Management Norwegian School of Economics Bergen Norway. SWPS University of Social Sciences and Humanities Warsaw Poland. Department of Psychological Sciences College of William and Mary Williamsburg VA USA. Department of Philosophy Macquarie University Sydney NSW Australia. Stanford Graduate School of Business Stanford University Stanford CA USA.

The COVID-19 pandemic has affected all domains of human life, including the economic and social fabric of societies. One of the central strategies for managing public health throughout the pandemic has been through persuasive messaging and collective behaviour change. To help scholars better understand the social and moral psychology behind public health behaviour, we present a dataset comprising of 51,404 individuals from 69 countries. This dataset was collected for the International Collaboration on Social & Moral Psychology of COVID-19 project (ICSMP COVID-19). This social science survey invited participants around the world to complete a series of moral and psychological measures and public health attitudes about COVID-19 during an early phase of the COVID-19 pandemic (between April and June 2020). The survey included seven broad categories of questions: COVID-19 beliefs and compliance behaviours; identity and social attitudes; ideology; health and well-being; moral beliefs and motivation; personality traits; and demographic variables. We report both raw and cleaned data, along with all survey materials, data visualisations, and psychometric evaluations of key variables.

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Optimizing collaborative sparse dictionary for compressive light field photography

Optimizing collaborative sparse dictionary for compressive l...

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IEEE Visual Communications and Image Processing (VCIP)

作者： Xiuhuan Zang Yunhui Shi Jin Wang Wenpeng Ding Baocai Yin Beijing Advanced Innovation Center for Future Internet Technology Beijing Key Laboratory of Multimedia and Intelligent Software Technology School of Software Engineering Beijing University of Technology Beijing China College of Computer Science and Technology Dalian University of Technology Dalian China

ISBN: (纸本)9781509053179

Compressive light field photography has gained a significant research interest during the past years. One important problem in light field images is the effective representation of the structures. In this paper, based on collaborative projection and sparse dictionary, we propose a light field reconstruction optimization scheme for compressive light field photography. By utilizing the special structural feature of high correlations among light field views, an optimized structured dictionary is proposed, which is more memory and time efficient compared with general sparse dictionary. Furthermore, we propose the corresponding structured dictionary learning model and efficient algorithm to train the optimized dictionary with fixed projection. Simulation results on light field data set demonstrate the effectiveness of our optimizing scheme in terms of reconstruction quality compared with general sparse dictionary.

关键词： Dictionaries Image reconstruction Training Collaboration Photography Algorithm design and analysis Compressed sensing

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Author Correction: National identity predicts public health support during a global pandemic

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Nature communications 2022年第1期13卷 1949页

作者： Jay J Van Bavel Aleksandra Cichocka Valerio Capraro Hallgeir Sjåstad John B Nezlek Tomislav Pavlović Mark Alfano Michele J Gelfand Flavio Azevedo Michèle D Birtel Aleksandra Cislak Patricia L Lockwood Robert Malcolm Ross Koen Abts Elena Agadullina John Jamir Benzon Aruta Sahba Nomvula Besharati Alexander Bor Becky L Choma Charles David Crabtree William A Cunningham Koustav De Waqas Ejaz Christian T Elbaek Andrej Findor Daniel Flichtentrei Renata Franc Biljana Gjoneska June Gruber Estrella Gualda Yusaku Horiuchi Toan Luu Duc Huynh Agustin Ibanez Mostak Ahamed Imran Jacob Israelashvili Katarzyna Jasko Jaroslaw Kantorowicz Elena Kantorowicz-Reznichenko André Krouwel Michael Laakasuo Claus Lamm Caroline Leygue Ming-Jen Lin Mohammad Sabbir Mansoor Antoine Marie Lewend Mayiwar Honorata Mazepus Cillian McHugh John Paul Minda Panagiotis Mitkidis Andreas Olsson Tobias Otterbring Dominic J Packer Anat Perry Michael Bang Petersen Arathy Puthillam Julián C Riaño-Moreno Tobias Rothmund Hernando Santamaría-García Petra C Schmid Drozdstoy Stoyanov Shruti Tewari Bojan Todosijević Manos Tsakiris Hans H Tung Radu G Umbreș Edmunds Vanags Madalina Vlasceanu Andrew Vonasch Meltem Yucel Yucheng Zhang Mohcine Abad Eli Adler Narin Akrawi Hamza Alaoui Mdarhri Hanane Amara David M Amodio Benedict G Antazo Matthew Apps F Ceren Ay Mouhamadou Hady Ba Sergio Barbosa Brock Bastian Anton Berg Maria P Bernal-Zárate Michael Bernstein Michał Białek Ennio Bilancini Natalia Bogatyreva Leonardo Boncinelli Jonathan E Booth Sylvie Borau Ondrej Buchel C Daryl Cameron Chrissie F Carvalho Tatiana Celadin Chiara Cerami Hom Nath Chalise Xiaojun Cheng Luca Cian Kate Cockcroft Jane Conway Mateo Andres Córdoba-Delgado Chiara Crespi Marie Crouzevialle Jo Cutler Marzena Cypryańska Justyna Dabrowska Michael A Daniels Victoria H Davis Pamala N Dayley Sylvain Delouvee Ognjan Denkovski Guillaume Dezecache Nathan A Dhaliwal Alelie B Diato Roberto Di Paolo Marianna Drosinou Uwe Dulleck Jānis Ekmanis Arhan S Ertan Tom W Etienne Hapsa Hossain Farhana Fahima Farkhari Har Department of Psychology and Neural Science New York University New York NY USA. jay.vanbavel@nyu.edu. School of Psychology University of Kent Canterbury England. Department of Economics Middlesex University London London England. Department of Strategy and Management Norwegian School of Economics Bergen Norway. SWPS University of Social Sciences and Humanities Poznań Poland. Department of Psychological Sciences College of William and Mary Williamsburg VA USA. Institute of Social Sciences Ivo Pilar Zagreb Croatia. Department of Philosophy Macquarie University Sydney NSW Australia. Stanford Graduate School of Business Stanford University Stanford CA USA. Institute of Communication Science Friedrich-Schiller University Jena Jena Germany. flavio.azevedo@uni-jena.de. School of Human Sciences Institute for Lifecourse Development University of Greenwich London England. Department of Experimental Psychology University of Oxford Oxford England. Center for Human Brain Health School of Psychology University of Birmingham Birmingham England. Department of Psychology Macquarie University Sydney NSW Australia. KU Leuven Leuven Belgium. National Research University Higher School of Economics (HSE) Moscow Russia. De La Salle University Manila Philippines. Department of Psychology University of the Witwatersrand Johannesburg South Africa. Department of Political Science Aarhus University Aarhus Denmark. X University Toronto ON Canada. Department of Government Dartmouth College Hanover NH USA. Department of Psychology University of Toronto Toronto ON Canada. Gatton College of Business and Economics University of Kentucky Lexington KY USA. Department of Mass Communication National University of Science and Technology (NUST) Islamabad Pakistan. Department of Management Aarhus University Aarhus Denmark. Faculty of Social and Economic Sciences Comenius University Bratislava Slovakia. IntraMed Buenos Aires Argentina. Macedonian Academy of Sciences and

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Correction to: Sequence-specific backbone resonance assignments and microsecond timescale molecular dynamics simulation of human eosinophil-derived neurotoxin

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Biomolecular NMR assignments 2018年第2期12卷 365-367页

作者： Donald Gagné Chitra Narayanan Khushboo Bafna Laurie-Anne Charest Pratul K Agarwal Nicolas Doucet INRS-Institut Armand-Frappier Université du Québec 531 Boulevard des Prairies Laval QC H7V 1B7 Canada. Structural Biology Initiative CUNY Advanced Science Research Center New York NY 10031 USA. Graduate School of Genome Science and Technology University of Tennessee Knoxville TN 37996 USA. Computational Biology Institute and Computer Science and Mathematics Division Oak Ridge National Laboratory 1 Bethel Valley Road Oak Ridge TN 37830 USA. Department of Biochemistry Cellular and Molecular Biology University of Tennessee Knoxville TN 37996 USA. INRS-Institut Armand-Frappier Université du Québec 531 Boulevard des Prairies Laval QC H7V 1B7 Canada. nicolas.doucet@iaf.inrs.ca. PROTEO The Québec Network for Research on Protein Function Engineering and Applications Université Laval 1045 Avenue de la Médecine Quebec QC G1V 0A6 Canada. nicolas.doucet@iaf.inrs.ca. GRASP The Groupe de recherche Axé sur la Structure des Protéines McGill University 3649 Promenade Sir William Osler Montreal QC H3G 0B1 Canada. nicolas.doucet@iaf.inrs.ca.

After publication of this article, the authors noticed that a N-C dimension error was unwillingly coded in the 3D NMR spectrum "***" processing script used to perform backbone assignments for this enzyme. The authors noticed that some OBS, CAR and LAB values in the "***" had been switched in the y and z dimensions, probably resulting from a wrong NMRPipe selection when reading the Varian NMR experimental parameters. They have carefully re-processed, re-analyzed, re-assigned, in addition to checking all scripts to evaluate the extent of this processing error on the published assignments. Authors determined that the "***" error resulted in a significant number of incorrect backbone resonance assignments, requiring us to issue corrections in Figs. 2, 3 and 4 of this published manuscript, in addition to Table S1. New versions of these figures and table are provided below. The corresponding BMRB entry has also been revised. The authors note that these modifications do not change the global message, conclusions, and molecular dynamics simulations presented in this article. The authors are grateful to David N. Bernard (INRS) for help with finding and correcting these errors.

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An extended catalog of galaxy-galaxy strong gravitational lenses discovered in DES using convolutional neural networks

arXiv

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arXiv 2019年

作者： Jacobs, C. Collett, T. Glazebrook, K. Buckley-Geer, E. Diehl, H.T. Lin, H. McCarthy, C. Qin, A.K. Odden, C. Caso Escudero, M. Dial, P. Yung, V.J. Gaitsch, S. Pellico, A. Lindgren, K.A. Abbott, T.M.C. Annis, J. Avila, S. Brooks, D. Burke, D.L. Carnero Rosell, A. Carrasco Kind, M. Carretero, J. da Costa, L.N. de Vicente, J. Fosalba, P. Frieman, J. García-Bellido, J. Gaztanaga, E. Goldstein, D.A. Gruen, D. Gruendl, R.A. Gschwend, J. Hollowood, D.L. Honscheid, K. Hoyle, B. James, D.J. Krause, E. Kuropatkin, N. Lahav, O. Lima, M. Maia, M.A.G. Marshall, J.L. Miquel, R. Plazas, A.A. Roodman, A. Sanchez, E. Scarpine, V. Serrano, S. Sevilla-Noarbe, I. Smith, M. Sobreira, F. Suchyta, E. Swanson, M.E.C. Tarle, G. Vikram, V. Walker, A.R. Zhang, Y. Centre for Astrophysics and Supercomputing Swinburne University of Technology P.O. Box 218 HawthornVIC3122 Australia Swinburne University of Technology HawthornVIC3122 Australia Institute of Cosmology & Gravitation University of Portsmouth Portsmouthpo1 3fx United Kingdom Fermi National Accelerator Laboratory P. O. Box 500 BataviaIL60510 United States School of Software and Electrical Engineering Swinburne University of Technology P.O. Box 218 HawthornVIC3122 Australia Phillips Academy AndoverMA01810 United States Cerro Tololo Inter-American Observatory National Optical Astronomy Observatory Casilla 603 La Serena Chile Fermi National Accelerator Laboratory P. O. Box 500 BataviaIL60510 United States Instituto de Fisica Teorica UAM/CSIC Universidad Autonoma de Madrid Madrid28049 Spain Department of Physics & Astronomy University College London Gower Street LondonWC1E 6BT United Kingdom Kavli Institute for Particle Astrophysics & Cosmology Stanford University P. O. Box 2450 StanfordCA94305 United States SLAC National Accelerator Laboratory Menlo ParkCA94025 United States Madrid Spain Laboratório Interinstitucional de e-Astronomia - LIneA Rua Gal. José Cristino 77 Rio de Janeiro RJ20921-400 Brazil Department of Astronomy University of Illinois at Urbana-Champaign 1002 W. Green Street UrbanaIL61801 United States National Center for Supercomputing Applications 1205 West Clark St. UrbanaIL61801 United States Barcelona Institute of Science and Technology Campus UAB Bellaterra [Barcelona08193 Spain Observatório Nacional Rua Gal. José Cristino 77 Rio de Janeiro RJ20921-400 Brazil Barcelona08034 Spain Campus UAB Carrer de Can Magrans s/n Barcelona08193 Spain Kavli Institute for Cosmological Physics University of Chicago ChicagoIL60637 United States California Institute of Technology 1200 East California Blvd MC 249-17 PasadenaCA91125 United States Department of Physics Stanford University 382 Via Pueblo Mall Sta

We search Dark Energy Survey (DES) Year 3 imaging for galaxy-galaxy strong gravitational lenses using convolutional neural networks, extending previous work with new training sets and covering a wider range of redshifts and colors. We train two neural networks using images of simulated lenses, then use them to score postage stamp images of 7.9 million sources from the Dark Energy Survey chosen to have plausible lens colors based on simulations. We examine 1175 of the highest-scored candidates and identify 152 probable or definite lenses. Examining an additional 20,000 images with lower scores, we identify a further 247 probable or definite candidates. After including 86 candidates discovered in earlier searches using neural networks and 26 candidates discovered through visual inspection of blue-near-red objects in the DES catalog, we present a catalog of 511 lens candidates. Copyright © 2019, The Authors. All rights reserved.

关键词： Surveys

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Quantum State Tomography via Reduced Density Matrices

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Physical Review Letters 2017年第2期118卷 020401-020401页

作者： Tao Xin Dawei Lu Joel Klassen Nengkun Yu Zhengfeng Ji Jianxin Chen Xian Ma Guilu Long Bei Zeng Raymond Laflamme State Key Laboratory of Low-Dimensional Quantum Physics and Department of Physics Tsinghua University Beijing 100084 China Institute for Quantum Computing University of Waterloo Waterloo Ontario N2L 3G1 Canada Department of Physics University of Guelph Guelph N1G 2W1 Ontario Canada Centre for Quantum Computation and Intelligent Systems Faculty of Engineering and Information Technology University of Technology Sydney New South Wales 2007 Australia Department of Mathematics and Statistics University of Guelph Guelph N1G 2W1 Ontario Canada State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences 100190 Beijing China Joint Center for Quantum Information and Computer Science University of Maryland College Park Maryland USA Department of Physics and Astronomy University of Waterloo Waterloo Ontario N2L 3G1 Canada Canadian Institute for Advanced Research Toronto M5G 1Z8 Ontario Canada Perimeter Institute for Theoretical Physics Waterloo Ontario N2L 2Y5 Canada

Quantum state tomography via local measurements is an efficient tool for characterizing quantum states. However, it requires that the original global state be uniquely determined (UD) by its local reduced density matrices (RDMs). In this work, we demonstrate for the first time a class of states that are UD by their RDMs under the assumption that the global state is pure, but fail to be UD in the absence of that assumption. This discovery allows us to classify quantum states according to their UD properties, with the requirement that each class be treated distinctly in the practice of simplifying quantum state tomography. Additionally, we experimentally test the feasibility and stability of performing quantum state tomography via the measurement of local RDMs for each class. These theoretical and experimental results demonstrate the advantages and possible pitfalls of quantum state tomography with local measurements.

关键词： Quantum entanglement Quantum information processing Quantum tomography Random matrix theory

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The 5th International Conference on Biomedical engineering and Biotechnology (ICBEB 2016) Abstracts

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BMC MEDICAL IMAGING 2016年第SUPPL 1期16卷 65-65页

作者： [Anonymous] Department of MRI Shandong Medical Imaging Research Institute Affiliated to Shandong University Jinan Shandong 250021 People’s Republic of China Department of Interventional Radiology Shandong Provincial Hospital Affiliated to Shandong University Jinan Shandong 250021 People’s Republic of China College of Information Science and Technology Engr. Research Center of Digitized Textile & Fashion Tech. for Ministry of Education Donghua University Shanghai 201620 China Intelligent multimedia information processing Lab College of Software Northeastern University Shenyang Liaoning Province 110004 China Institute of Biomedical and Health Engineering Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China School of Computer Science and Technology Nanjing Normal University Nanjing China Department of Electrical Engineering The City College of New York CUNY New York USA Jiangsu Key Laboratory of 3D Printing Equipment and Manufacturing Nanjing China School of Electronic Science and Engineering Nanjing University Nanjing Jiangsu 210046 China College of Engineering Nanyang Technological University Singapore 639798 Singapore School of Electronic Information Shanghai Dianji University Shanghai China School of Natural Sciences and Mathematics Shepherd University Shepherdstown WV 25443 USA Davis College of Agriculture Natural Resources and Design West Virginia University Morgantown WV 26505 USA State Key Laboratory of Millimeter Waves Southeast University Nanjing 210096 China Center of Medical Physics and Technology Hefei Institutes of Physical Science Chinese Academy of Sciences Hefei China College of Agricultural and Life Sciences University of Florida Gainesville FL 32611 USA Courant Institute of Mathematical Sciences New York University New York NY 10012 USA Translational Imaging Division & MRI Unit Columbia University and New York State Psychiatric Institute New York NY 10032 USA Guangxi Key Laboratory of Manufacturing System & Adv

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