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Tomographic reconstruction of time-bin-entangled qudits

Physical Review A 2016年第4期94卷 042328-042328页

作者： Samantha J. Nowierski Neal N. Oza Prem Kumar Gregory S. Kanter Center for Photonic Communication and Computing EECS Department Northwestern University 2145 Sheridan Road Evanston Illinois 60208-3118 USA Graduate Program in Applied Physics Northwestern University Evanston Illinois 60208 USA Department of Physics and Astronomy Northwestern University 2145 Sheridan Road Evanston Illinois 60208-3112 USA

We describe an experimental implementation to generate and measure high-dimensional time-bin-entangled qudits. Two-photon time-bin entanglement is generated via spontaneous four-wave mixing in single-mode fiber. Unbalanced Mach-Zehnder interferometers transform selected time bins to polarization entanglement, allowing standard polarization-projective measurements to be used for complete quantum state tomographic reconstruction. Here we generate maximally entangled qubits (d=2), qutrits (d=3), and ququarts (d=4), as well as other phase-modulated nonmaximally entangled qubits and qutrits. We reconstruct and verify all generated states using maximum-likelihood estimation tomography.

关键词： Entanglement detection Entanglement manipulation Quantum entanglement Quantum tomography

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Exploring cloud elasticity on developing an EPCGlobal-compliant middleware

Exploring cloud elasticity on developing an EPCGlobal-compli...

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IEEE International Conference on RFID

作者： Rodrigo da Rosa Righi Eduardo Souza dos Reis Gustavo Rostirolla Cristiano André da Costa Antonio Marcos Alberti Applied Computing Graduate Program Universidade do Vale do Rio dos Sinos (Unisinos) São Leopoldo RC Brazil Instituto Nacional de Telecomunições (Inatel) Santa Rita do Sapucaí MG Brazil

The digital universe is growing at significant rates in recent years. One of the main responsible for this sentence is the Internet of Things (IoT), which requires middlewares capable of handling this increase of data volume in real-time. Solutions modeled at software, hardware and/or architecture level present limitations to handle such load, facing a scalability problem in the IoT scope. In this context, this article presents a model named Eliot (Elasticity-driven Internet of Things) which combines both cloud and high performance computing to address the IoT scalability problem in EPCglobal-compliant architectures. Based on the Eliot model, we developed a prototype that can run as a plugin solution together with any current EPCglobal-compliant middleware. The results are encouraging, presenting significant performance gains when comparing both elastic and non-elastic executions.

关键词： Elasticity Internet of things Monitoring Cloud computing Radiofrequency identification Computer architecture Load modeling

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Cloud elasticity for HPC applications: Observing energy, performance and cost

Cloud elasticity for HPC applications: Observing energy, per...

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Conferencia Latinoamericana En Informatica (CLEI)

作者： Vinicius Facco Rodrigues Gustavo Rostirolla Rodrigo da Rosa Righi Cristiano André da Costa Jorge Luis Victoria Barbosa Applied Computing Graduate Program Unisinos São Leopoldo RS Brazil Applied Computing Graduate Program Unisinos RS Brazil

Elasticity is one of the most known capabilities related to cloud computing, being largely deployed using thresholds. In this way, limits are used to drive resource mangement actions, leading to the following problem statements: How can cloud users set the threshold values to enable elasticity in their cloud applications? And what is the impact of the application's load pattern in the elasticity? This article answers these questions for iterative high performance computing applications, showing the impact of both thresholds and load patterns on application performance and resource consumption. To accomplish this, we developed a reactive and PaaS-based elasticity model called AutoElastic and employed it over a private cloud to execute a numerical integration application. Here, we are presenting an analysis of best practices and possible optimizations regarding the elasticity and HPC pair. Considering the results, we observed that the upper threshold influences the application time more than the lower one.

关键词： Cloud computing Elasticity Computational modeling Manuals Monitoring High performance computing

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Climate Precipitation Prediction by Neural Network

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Journal of Mathematics and System Science 2015年第5期5卷 207-213页

作者： Juliana Aparecida Anochi Haroldo Fraga de Campos Velho Applied Computing Graduate Program National Institute for Space Research (INPE) Brazil. Associated Laboratory for Computing and Applied Mathematics National Institute for Space Research (INPE).

In this work a neural network model for climate forecasting is presented. The model is built by training a neural network with available reanalysis data. In order to assess the model, the development methodology considers the use of data reduction strategies that eliminate data redundancy thus reducing the complexity of the models. The results presented in this paper considered the use of Rough Sets Theory principles in extracting relevant information from the available data to achieve the reduction of redundancy among the variables used for forecasting purposes. The paper presents results of climate prediction made with the use of the neural network based model. The results obtained in the conducted experiments show the effectiveness of the methodology, presenting estimates similar to observations.

关键词： Climate Prediction Neural Networks Rough Sets Theory

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SPT clusters with DES and HST weak lensing. II. Cosmological constraints from the abundance of massive halos

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Physical Review D 2024年第8期110卷 083510页

作者： S. Bocquet S. Grandis L. E. Bleem M. Klein J. J. Mohr T. Schrabback T. M. C. Abbott P. A. R. Ade M. Aguena A. Alarcon S. Allam S. W. Allen O. Alves A. Amon A. J. Anderson J. Annis B. Ansarinejad J. E. Austermann S. Avila D. Bacon M. Bayliss J. A. Beall K. Bechtol M. R. Becker A. N. Bender B. A. Benson G. M. Bernstein S. Bhargava F. Bianchini M. Brodwin D. Brooks L. Bryant A. Campos R. E. A. Canning J. E. Carlstrom A. Carnero Rosell M. Carrasco Kind J. Carretero F. J. Castander R. Cawthon C. L. Chang C. Chang P. Chaubal R. Chen H. C. Chiang A. Choi T-L. Chou R. Citron C. Corbett Moran J. Cordero M. Costanzi T. M. Crawford A. T. Crites L. N. da Costa M. E. S. Pereira C. Davis T. M. Davis J. DeRose S. Desai T. de Haan H. T. Diehl M. A. Dobbs S. Dodelson C. Doux A. Drlica-Wagner K. Eckert J. Elvin-Poole S. Everett W. Everett I. Ferrero A. Ferté A. M. Flores J. Frieman J. Gallicchio J. García-Bellido M. Gatti E. M. George G. Giannini M. D. Gladders D. Gruen R. A. Gruendl N. Gupta G. Gutierrez N. W. Halverson I. Harrison W. G. Hartley K. Herner S. R. Hinton G. P. Holder D. L. Hollowood W. L. Holzapfel K. Honscheid J. D. Hrubes N. Huang J. Hubmayr E. M. Huff D. Huterer K. D. Irwin D. J. James M. Jarvis G. Khullar K. Kim L. Knox R. Kraft E. Krause K. Kuehn N. Kuropatkin F. Kéruzoré O. Lahav A. T. Lee P.-F. Leget D. Li H. Lin A. Lowitz N. MacCrann G. Mahler A. Mantz J. L. Marshall J. McCullough M. McDonald J. J. McMahon J. Mena-Fernández F. Menanteau S. S. Meyer R. Miquel J. Montgomery J. Myles T. Natoli A. Navarro-Alsina J. P. Nibarger G. I. Noble V. Novosad R. L. C. Ogando Y. Omori S. Padin S. Pandey P. Paschos S. Patil A. Pieres A. A. Plazas Malagón A. Porredon J. Prat C. Pryke M. Raveri C. L. Reichardt J. Roberson R. P. Rollins C. Romero A. Roodman J. E. Ruhl E. S. Rykoff B. R. Saliwanchik L. Salvati C. Sánchez E. Sanchez D. Sanchez Cid A. Saro K. K. Schaffer L. F. Secco I. Sevilla-Noarbe K. Sharon E. Sheldon T. Shin C. Sievers G. Smecher M. Smith T. Somboonpanyakul M. Sommer B. Stalder A. A. Stark J. Stephen V. Straz University Observatory Faculty of Physics Universität Innsbruck Institut für Astro- und Teilchenphysik Technikerstraße 25/8 6020 Innsbruck Austria High-Energy Physics Division Argonne National Laboratory 9700 South Cass Avenue Lemont Illinois 60439 USA Kavli Institute for Cosmological Physics University of Chicago 5640 South Ellis Avenue Chicago Illinois 60637 USA Max Planck Institute for Extraterrestrial Physics Gießenbachstraße 1 85748 Garching Germany Argelander-Institut für Astronomie Auf dem Hügel 71 53121 Bonn Germany Cerro Tololo Inter-American Observatory NSF’s National Optical-Infrared Astronomy Research Laboratory Casilla 603 La Serena Chile School of Physics and Astronomy Cardiff University Cardiff CF24 3YB United Kingdom Laboratório Interinstitucional de e-Astronomia—LIneA Rua Gal. José Cristino 77 Rio de Janeiro Rio de Janeiro—20921-400 Brazil Fermi National Accelerator Laboratory P. O. Box 500 Batavia Illinois 60510 USA Kavli Institute for Particle Astrophysics and Cosmology Stanford University 452 Lomita Mall Stanford California 94305 USA Department of Physics Stanford University 382 Via Pueblo Mall Stanford California 94305 USA SLAC National Accelerator Laboratory 2575 Sand Hill Road Menlo Park California 94025 USA Department of Physics University of Michigan Ann Arbor Michigan 48109 USA Institute of Astronomy University of Cambridge Madingley Road Cambridge CB3 0HA United Kingdom Kavli Institute for Cosmology University of Cambridge Madingley Road Cambridge CB3 0HA United Kingdom School of Physics University of Melbourne Parkville Victoria 3010 Australia NIST Quantum Devices Group 325 Broadway Mailcode 817.03 Boulder Colorado 80305 USA Department of Physics University of Colorado Boulder Colorado 80309 USA Institut de Física d’Altes Energies (IFAE) The Barcelona Institute of Science and Technology Campus UAB 08193 Bellaterra (Barcelona) Spain Institute of Cosmology and Gravitation University of Portsmouth Portsmouth

We present cosmological constraints from the abundance of galaxy clusters selected via the thermal Sunyaev-Zel’dovich (SZ) effect in South Pole Telescope (SPT) data with a simultaneous mass calibration using weak gravitational lensing data from the Dark Energy Survey (DES) and the Hubble Space Telescope (HST). The cluster sample is constructed from the combined SPT-SZ, SPTpol ECS, and SPTpol 500d surveys, and comprises 1,005 confirmed clusters in the redshift range 0.25–1.78 over a total sky area of 5200 deg2. We use DES Year 3 weak-lensing data for 688 clusters with redshifts z<0.95 and HST weak-lensing data for 39 clusters with 0.6

关键词： Cosmological parameters Dark energy Large scale structure of the Universe Galaxy clusters

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Developing "Critical Thinking Skills" in Graduate Engineering program 122

Developing "Critical Thinking Skills" in Graduate Engineerin...

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2015 122nd ASEE Annual Conference and Exposition

作者： Viswanathan, Shekar Radhakrishnan, Ben D. National University Department of Applied Engineering CA United States National University MS Sustainability Management Program School of Engineering and Computing San DiegoCA United States

This paper provides a review of two programs incorporating "critical thinking skills" as a major focus. In addition, this paper illustrates examples of structured assignments and novel exercises that were developed and implemented to promote "critical thinking skills." Also, special rubrics developed to measure "critical thinking skills" are illustrated. This paper describes Student Centric Learning (SCL) with its four categories of implementation. It also demonstrates that SCL is a strong enabler for developing, implementing, and instilling critical thinking skills. Based on the findings, that gamification along with SCL with its four categories of implementation really form the four pillars and serves as a strong enabler for developing, implementing, and instilling critical thinking skills. © American Society for Engineering Education, 2015.

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SciPy 1.0—Fundamental algorithms for scientific computing in python

arXiv

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arXiv 2019年

作者： Virtanen, Pauli Gommers, Ralf Oliphant, Travis E. Haberland, Matt Reddy, Tyler Cournapeau, David Burovski, Evgeni Peterson, Pearu Weckesser, Warren Bright, Jonathan van der Walt, Stéfan J. Brett, Matthew Wilson, Joshua Millman, K. Jarrod Mayorov, Nikolay Nelson, Andrew R.J. Jones, Eric Kern, Robert Larson, Eric Carey, C.J. Polat, Ilhan Feng, Yu Moore, Eric W. VanderPlas, Jake Laxalde, Denis Perktold, Josef Cimrman, Robert Henriksen, Ian Quintero, E.A. Harris, Charles R. Archibald, Anne M. Ribeiro, Antônio H. Pedregosa, Fabian van Mulbregt, Paul University of Jyväskylä University of Jyväskylä FI-40014 Finland Quansight LLC AustinTX United States Ultrasound Imaging Mayo Clinic RochesterMN55902 United States Electrical Engineering Brigham Young University ProvoUT84604 United States Enthought Inc. AustinTX78701 United States Anaconda Inc AustinTX78701 United States BioResource and Agricultural Engineering Department California Polytechnic State University San Luis ObispoCA93407 United States Department of Mathematics University of California Los AngelesCA90025 United States Los Alamos National Laboratory Los AlamosNM87544 United States Independent Researcher Higher School of Economics Myasnitskaya 20 Moscow101000 Russia Independent Researcher Saue Estonia Department of Mechanics and Applied Mathematics Institute of Cybernetics Tallinn Technical University Akadeemia Rd 21 Tallinn Estonia Independent Researcher NY United States Berkeley Institute for Data Science University of California BerkeleyCA94720 United States School of Psychology University of Birmingham Edgbaston BirmighamB15 2TT United Kingdom Division of Biostatistics University of California BerkeleyCA94720 United States WayRay LLC Skolkovo Innovation Center Moscow143026 Russia Australian Nuclear Science and Technology Organisation Locked Bag 2001 Kirrawee DCNSW2232 Australia Institute for Learning and Brain Sciences University of Washington SeattleWA98195 United States College of Information and Computing Sciences University of Massachusetts Amherst AmherstMA01002 United States Berkeley Center for Cosmological Physics University of California BerkeleyCA94720 United States Bruker Biospin Corp. 15 Fortune Drive BillericaMA01821 United States University of Washington SeattleWA98195 United States New Technologies - Research Centre University of West Bohemia Univerzitní 8 Plzeň306 14 Czech Republic Oden Institute for Computational Engineering and Sciences University of Texas at Austin AustinTX7

SciPy is an open source scientific computing library for the Python programming language. SciPy 1.0 was released in late 2017, about 16 years after the original version 0.1 release. SciPy has become a de facto standard for leveraging scientific algorithms in the Python programming language, with more than 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories, and millions of downloads per year. This includes usage of SciPy in almost half of all machine learning projects on GitHub, and usage by high profile projects including LIGO gravitational wave analysis and creation of the first-ever image of a black hole (M87). The library includes functionality spanning clustering, Fourier transforms, integration, interpolation, file I/O, linear algebra, image processing, orthogonal distance regression, minimization algorithms, signal processing, sparse matrix handling, computational geometry, and statistics. In this work, we provide an overview of the capabilities and development practices of the SciPy library and highlight some recent technical developments. Copyright © 2019, The Authors. All rights reserved.

关键词： Open source software

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Multi-level computational methods for interdisciplinary research in the hathi trust digital library

arXiv

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arXiv 2017年

作者： Murdock, Jaimie Allen, Colin Borner, Katy Light, Robert McAlister, Simon Ravenscroft, Andrew Rose1, Robert Rose, Doori Otsuka, Jun Bourget, David Lawrence, John Reed, Chris Program in Cognitive Science Indiana University BloomingtonIN United States School of Informatics and Computing Indiana University BloomingtonIN United States Department of History and Philosophy of Science and Medicine Indiana University BloomingtonIN United States Indiana University Network Science Institute IUNI BloomingtonIN United States User-Centered Social Media Department of Computer Science and Applied Cognitive Science University of Duisburg-Essen Duisburg Germany International Centre for Public Pedagogy ICPuP Cass School of Education and Communities University of East London London Department of Mathematics Indiana University BloomingtonIN United States Department of Philosophy Kyoto University Kyoto Japan Department of Philosophy University of Western Ontario LondonON Canada Centre for G Technology University of Dundee Dundee United Kingdom

We show how faceted search using a combination of traditional classification sys-tems and mixed-membership topic models can go beyond keyword search to inform re-source discovery, hypothesis formulation, and argument extraction for interdisciplinary research. Our test domain is the history and philosophy of scientific work on animal mind and cognition. The methods can be generalized to other research areas and ul-timately support a system for semi-automatic identification of argument structures. We provide a case study for the application of the methods to the problem of identi-fying and extracting arguments about anthropomorphism during a critical period in the development of comparative psychology. We show how a combination of classifi-cation systems and mixed-membership models trained over large digital libraries can inform resource discovery in this domain. Through a novel approach of \drill-down" topic modeling|simultaneously reducing both the size of the corpus and the unit of analysis|we are able to reduce a large collection of fulltext volumes to a much smaller set of pages within six focal volumes containing arguments of interest to historiansand philosophers of comparative psychology. The volumes identified in this way did not appear among the first ten results of the keyword search in the HathiTrust digital library and the pages bear the kind of \close reading" needed to generate original in-terpretations that is the heart of scholarly work in the humanities. Zooming back out, we provide a way to place the books onto a map of science originally constructed from very different data and for different purposes. The multilevel approach advances un-derstanding of the intellectual and societal contexts in which writings are interpreted. Copyright © 2017, The Authors. All rights reserved.

关键词： Digital libraries

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Correction: X-chromosome-linked miR548am-5p is a key regulator of sex disparity in the susceptibility to mitochondria-mediated apoptosis

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Cell death & disease 2019年第11期10卷 828页

作者： Paola Matarrese Paolo Tieri Simona Anticoli Barbara Ascione Maria Conte Claudio Franceschi Walter Malorni Stefano Salvioli Anna Ruggieri Center for Gender Specific Medicine Istituto Superiore di Sanità viale Regina Elena 299 Rome Italy. CNR National Research Council IAC Institute for Applied Computing Via dei Taurini 19 Rome Italy. Data Science Program La Sapienza University of Rome Rome Italy. Department of Experimental Diagnostic and Specialty Medicine (DIMES) University of Bologna Bologna Italy. Interdepartmental Centre "L. Galvani" (CIG) University of Bologna via San Giacomo 12 40126 Bologna Italy. IRCCS Istituto delle Scienze Neurologiche di Bologna Via Altura 3 40139 Bologna Italy. Lobachevsky State University of Nizhny Novgorod Nizhny Novgorod Russia. School of Mathematical Physical and Natural Sciences and Faculty of Medicine University of Tor Vergata Rome Italy. Department of Experimental Diagnostic and Specialty Medicine (DIMES) University of Bologna Bologna Italy. stefano.salvioli@unibo.it. Interdepartmental Centre "L. Galvani" (CIG) University of Bologna via San Giacomo 12 40126 Bologna Italy. stefano.salvioli@unibo.it. Center for Gender Specific Medicine Istituto Superiore di Sanità viale Regina Elena 299 Rome Italy. anna.ruggieri@iss.it.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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On using fuzzy logic to control a simulated hexacopter carrying an attached pendulum

On using fuzzy logic to control a simulated hexacopter carry...

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Latin America Congress on Computational Intelligence (LA-CCI)

作者： Emanoel Koslosky Marco A. Wehrmeister João A. Fabro André S. de Oliveira Graduate Program in Applied Computing (PPGCA) Federal University of Technology Curitiba Brazil

Fuzzy logic is used in many applications from industrial process control to automotive applications, including consumers trend forecast, aircraft maneuvering control and others. Considering the increased interest in using of multi-rotor aircrafts (usually called drones) for many kinds of applications, it is important to study new methods to improve multi-rotor maneuverability while controlling its stability in a proper way. Controlling the flight of multi-rotors, specially those equipped six rotors, is not a trivial task. When considering the design of such a control systems, traditional approaches such as PD/PID are very difficult to design, in spite of being easily implementable. This work proposes an approach based on multiple interconnected fuzzy controllers, aiming to control the various aspects related to maneuverability of a hexacopter carrying a free payload forming a pendulum. The behavior produced by such a control system has been simulated on a well-known robotics simulation environment and analyzed in terms of flight stability, as well as roll, pitch and yaw movements. The results show the feasibility of the proposed approach in keeping the hexacopter flying in a stable way.

关键词： Rotors Acceleration Payloads Control systems Helicopters Sensors

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