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Observation and measurement of Higgs boson decays to WW* with the ATLAS detector

Physical Review D 2015年第1期92卷 012006-012006页

作者： G. Aad B. Abbott J. Abdallah S. Abdel Khalek O. Abdinov R. Aben B. Abi M. Abolins O. S. AbouZeid H. Abramowicz H. Abreu R. Abreu Y. Abulaiti B. S. Acharya L. Adamczyk D. L. Adams J. Adelman S. Adomeit T. Adye T. Agatonovic-Jovin J. A. Aguilar-Saavedra M. Agustoni S. P. Ahlen F. Ahmadov G. Aielli H. Akerstedt T. P. A. Åkesson G. Akimoto A. V. Akimov G. L. Alberghi J. Albert S. Albrand M. J. Alconada Verzini M. Aleksa I. N. Aleksandrov C. Alexa G. Alexander G. Alexandre T. Alexopoulos M. Alhroob G. Alimonti L. Alio J. Alison B. M. M. Allbrooke L. J. Allison P. P. Allport A. Aloisio A. Alonso F. Alonso C. Alpigiani A. Altheimer B. Alvarez Gonzalez M. G. Alviggi K. Amako Y. Amaral Coutinho C. Amelung D. Amidei S. P. Amor Dos Santos A. Amorim S. Amoroso N. Amram G. Amundsen C. Anastopoulos L. S. Ancu N. Andari T. Andeen C. F. Anders G. Anders K. J. Anderson A. Andreazza V. Andrei X. S. Anduaga S. Angelidakis I. Angelozzi P. Anger A. Angerami F. Anghinolfi A. V. Anisenkov N. Anjos A. Annovi M. Antonelli A. Antonov J. Antos F. Anulli M. Aoki L. Aperio Bella G. Arabidze Y. Arai J. P. Araque A. T. H. Arce F. A. Arduh J-F. Arguin S. Argyropoulos M. Arik A. J. Armbruster O. Arnaez V. Arnal H. Arnold M. Arratia O. Arslan A. Artamonov G. Artoni S. Asai N. Asbah A. Ashkenazi B. Åsman L. Asquith K. Assamagan R. Astalos M. Atkinson N. B. Atlay B. Auerbach K. Augsten M. Aurousseau G. Avolio B. Axen G. Azuelos Y. Azuma M. A. Baak A. E. Baas C. Bacci H. Bachacou K. Bachas M. Backes M. Backhaus E. Badescu P. Bagiacchi P. Bagnaia Y. Bai T. Bain J. T. Baines O. K. Baker P. Balek F. Balli E. Banas Sw. Banerjee A. A. E. Bannoura H. S. Bansil L. Barak S. P. Baranov E. L. Barberio D. Barberis M. Barbero T. Barillari M. Barisonzi T. Barklow N. Barlow S. L. Barnes B. M. Barnett R. M. Barnett Z. Barnovska A. Baroncelli G. Barone A. J. Barr F. Barreiro J. Barreiro Guimarães da Costa R. Bartoldus A. E. Barton P. Bartos V. Bartsch A. Bassalat A. Basye R. L. Bates S. J. Batista J. R. Batley M. Battaglia M. Battistin F. Bauer H. S. Bawa J. B. Bea CPPM Aix-Marseille Université and CNRS/IN2P3 Marseille France Homer L. Dodge Department of Physics and Astronomy University of Oklahoma Norman OK United States of America Institute of Physics Academia Sinica Taipei Taiwan LAL Université Paris-Sud and CNRS/IN2P3 Orsay France Institute of Physics Azerbaijan Academy of Sciences Baku Azerbaijan Nikhef National Institute for Subatomic Physics and University of Amsterdam Amsterdam Netherlands Department of Physics Oklahoma State University Stillwater OK United States of America Department of Physics and Astronomy Michigan State University East Lansing MI United States of America Department of Physics University of Toronto Toronto ON Canada Raymond and Beverly Sackler School of Physics and Astronomy Tel Aviv University Tel Aviv Israel Department of Physics Technion: Israel Institute of Technology Haifa Israel CERN Geneva Switzerland Department of Physics Stockholm University Sweden The Oskar Klein Centre Stockholm Sweden INFN Gruppo Collegato di Udine Sezione di Trieste Udine Italy ICTP Trieste Italy AGH University of Science and Technology Faculty of Physics and Applied Computer Science Krakow Poland Physics Department Brookhaven National Laboratory Upton NY United States of America Department of Physics Northern Illinois University DeKalb IL United States of America Fakultät für Physik Ludwig-Maximilians-Universität München München Germany Particle Physics Department Rutherford Appleton Laboratory Didcot United Kingdom Institute of Physics University of Belgrade Belgrade Serbia Laboratorio de Instrumentacao e Fisica Experimental de Particulas - LIP Lisboa Portugal Departamento de Fisica Teorica y del Cosmos and CAFPE Universidad de Granada Granada Spain Albert Einstein Center for Fundamental Physics and Laboratory for High Energy Physics University of Bern Bern Switzerland Department of Physics Boston University Boston MA United States of America Joint Institute for Nuclear Research JINR Dubna D

We report the observation of Higgs boson decays to WW* based on an excess over background of 6.1 standard deviations in the dilepton final state, where the Standard Model expectation is 5.8 standard deviations. Evidence for the vector-boson fusion (VBF) production process is obtained with a significance of 3.2 standard deviations. The results are obtained from a data sample corresponding to an integrated luminosity of 25 fb−1 from s=7 and 8 TeV pp collisions recorded by the ATLAS detector at the LHC. For a Higgs boson mass of 125.36 GeV, the ratio of the measured value to the expected value of the total production cross section times branching fraction is 1.09−0.15+0.16(stat)−0.14+0.17(syst). The corresponding ratios for the gluon fusion and vector-boson fusion production mechanisms are 1.02±0.19(stat)−0.18+0.22(syst) and 1.27−0.40+0.44(stat)−0.21+0.30(syst), respectively. At s=8 TeV, the total production cross sections are measured to be σ(gg→H→WW*)=4.6±0.9(stat)−0.7+0.8(syst) pb and σ(VBF H→WW*)=0.51−0.15+0.17(stat)−0.08+0.13(syst) pb. The fiducial cross section is determined for the gluon-fusion process in exclusive final states with zero or one associated jet.

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Measurement of the transverse polarization of Λ and Λ¯ hyperons produced in proton-proton collisions at s=7 TeV using the ATLAS detector

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Physical Review D 2015年第3期91卷 032004-032004页

作者： G. Aad B. Abbott J. Abdallah S. Abdel Khalek O. Abdinov R. Aben B. Abi M. Abolins O. S. AbouZeid H. Abramowicz H. Abreu R. Abreu Y. Abulaiti B. S. Acharya L. Adamczyk D. L. Adams J. Adelman S. Adomeit T. Adye T. Agatonovic-Jovin J. A. Aguilar-Saavedra M. Agustoni S. P. Ahlen F. Ahmadov G. Aielli H. Akerstedt T. P. A. Åkesson G. Akimoto A. V. Akimov G. L. Alberghi J. Albert S. Albrand M. J. Alconada Verzini M. Aleksa I. N. Aleksandrov C. Alexa G. Alexander G. Alexandre T. Alexopoulos M. Alhroob G. Alimonti L. Alio J. Alison B. M. M. Allbrooke L. J. Allison P. P. Allport A. Aloisio A. Alonso F. Alonso C. Alpigiani A. Altheimer B. Alvarez Gonzalez M. G. Alviggi K. Amako Y. Amaral Coutinho C. Amelung D. Amidei S. P. Amor Dos Santos A. Amorim S. Amoroso N. Amram G. Amundsen C. Anastopoulos L. S. Ancu N. Andari T. Andeen C. F. Anders G. Anders K. J. Anderson A. Andreazza V. Andrei X. S. Anduaga S. Angelidakis I. Angelozzi P. Anger A. Angerami F. Anghinolfi A. V. Anisenkov N. Anjos A. Annovi M. Antonelli A. Antonov J. Antos F. Anulli M. Aoki L. Aperio Bella G. Arabidze Y. Arai J. P. Araque A. T. H. Arce F. A. Arduh J-F. Arguin S. Argyropoulos M. Arik A. J. Armbruster O. Arnaez V. Arnal H. Arnold M. Arratia O. Arslan A. Artamonov G. Artoni S. Asai N. Asbah A. Ashkenazi B. Åsman L. Asquith K. Assamagan R. Astalos M. Atkinson N. B. Atlay B. Auerbach K. Augsten M. Aurousseau G. Avolio B. Axen G. Azuelos Y. Azuma M. A. Baak A. E. Baas C. Bacci H. Bachacou K. Bachas M. Backes M. Backhaus E. Badescu P. Bagiacchi P. Bagnaia Y. Bai T. Bain J. T. Baines O. K. Baker P. Balek F. Balli E. Banas Sw. Banerjee A. A. E. Bannoura H. S. Bansil L. Barak S. P. Baranov E. L. Barberio D. Barberis M. Barbero T. Barillari M. Barisonzi T. Barklow N. Barlow S. L. Barnes B. M. Barnett R. M. Barnett Z. Barnovska A. Baroncelli G. Barone A. J. Barr F. Barreiro J. Barreiro Guimarães da Costa R. Bartoldus A. E. Barton P. Bartos A. Bassalat A. Basye R. L. Bates S. J. Batista J. R. Batley M. Battaglia M. Battistin F. Bauer H. S. Bawa J. B. Beacham M. D. CPPM Aix-Marseille Université and CNRS/IN2P3 Marseille France Homer L. Dodge Department of Physics and Astronomy University of Oklahoma Norman OK United States of America Institute of Physics Academia Sinica Taipei Taiwan LAL Université Paris-Sud and CNRS/IN2P3 Orsay France Institute of Physics Azerbaijan Academy of Sciences Baku Azerbaijan Nikhef National Institute for Subatomic Physics and University of Amsterdam Amsterdam Netherlands Department of Physics Oklahoma State University Stillwater OK United States of America Department of Physics and Astronomy Michigan State University East Lansing MI United States of America Department of Physics University of Toronto Toronto ON Canada Raymond and Beverly Sackler School of Physics and Astronomy Tel Aviv University Tel Aviv Israel Department of Physics Technion: Israel Institute of Technology Haifa Israel CERN Geneva Switzerland Department of Physics Stockholm University Sweden The Oskar Klein Centre Stockholm Sweden INFN Gruppo Collegato di Udine Sezione di Trieste Udine Italy ICTP Trieste Italy AGH University of Science and Technology Faculty of Physics and Applied Computer Science Krakow Poland Physics Department Brookhaven National Laboratory Upton NY United States of America Department of Physics Northern Illinois University DeKalb IL United States of America Fakultät für Physik Ludwig-Maximilians-Universität München München Germany Particle Physics Department Rutherford Appleton Laboratory Didcot United Kingdom Institute of Physics University of Belgrade Belgrade Serbia Laboratorio de Instrumentacao e Fisica Experimental de Particulas - LIP Lisboa Portugal Departamento de Fisica Teorica y del Cosmos and CAFPE Universidad de Granada Granada (Spain) Portugal Albert Einstein Center for Fundamental Physics and Laboratory for High Energy Physics University of Bern Bern Switzerland Department of Physics Boston University Boston MA United States of America Joint Institute for Nuclear Research JI

The transverse polarization of Λ and Λ¯ hyperons produced in proton-proton collisions at a center-of-mass energy of 7 TeV is measured. The analysis uses 760 μb−1 of minimum bias data collected by the ATLAS detector at the LHC in the year 2010. The measured transverse polarization averaged over Feynman xF from 5×10−5 to 0.01 and transverse momentum pT from 0.8 to 15 GeV is −0.010±0.005(stat)±0.004(syst) for Λ and 0.002±0.006(stat)±0.004(syst) for Λ¯. It is also measured as a function of xF and pT, but no significant dependence on these variables is observed. Prior to this measurement, the polarization was measured at fixed-target experiments with center-of-mass energies up to about 40 GeV. The ATLAS results are compatible with the extrapolation of a fit from previous measurements to the xF range covered by this measurement.

关键词： POLARIZATION (Nuclear physics) RESEARCH PROTON-proton interactions DETECTORS EXTRAPOLATION MASS (Physics) -- Measurement

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A self-healing single core architecture using dynamically reconfigurable devices

A self-healing single core architecture using dynamically re...

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2012 16th International Conference on System Theory, Control and Computing, ICSTCC 2012

作者： Popa, C. Stan, A. Gheorghe Asachi Technical University of Iasi Department of Computer Engineering and Applied Informatics Romania

ISBN: (纸本)9786068348483

The IT industry has been focusing for several years on providing to users and designers the possibility of creating software applications disregarding hardware resources. Multi-processor architectures seem to be more of interest in recent developments because of their capacity to exploit programmable parallelism at acceptable costs without posing severe software designing problems. But in any thinkable scenario, software will always be dependent on the hardware it is executing on. In another matter of speaking, hardware performances will always affect software's ability in providing results. There is also the question if the gathered results are correct or not, if the system that provides them is fast, safe and if it is a reliable and a maintainable one. This paper proposes a scalable architecture surrounding a single core microprocessor with the purpose of increasing computational speed and reliability. For achieving this, a flexible hardware platform would be appropriate, e.g. field programmable gate arrays (FPGAs). The single core system will revolve around a Picoblaze soft-core microprocessor. By generating a series of modules with the same functionality as the executing software, an N-module redundancy system will increase systems security and reliability. © 2012 Dunarea de Jos University.

关键词： Redundancy

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Choosing a Proper Control Structure for a Mechatronic System with Variable Parameters

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IFAC Proceedings Volumes 2013年第6期46卷 26-31页

作者： Alexandra-Iulia Stinean Stefan Preitl Radu-Emil Precup Claudia-Adina Dragos Emil M. Petriu Mircea-Bogdan Radac Department of Automation and Applied Informatics “Politehnica” University of Timisoara Bd. V. Parvan 2 RO-300223 Timisoara Romania (Tel: +40-256403224) School of Electrical Engineering and Computer Science University of Ottawa 800 King Edward Ottawa ON K1N 6N5 Canada

The paper presents design methods and control structure solutions dedicated to servo systems with continuously variable parameters. In order to obtain high control performance for the strip winding system – speed control – four cascade control structures (CCS) (with a inner proportional-integral (PI) current controller) with bump-less switching between several control algorithms are developed and tested. These solutions prove simplicity in adaptation on the representative operating points. The current controller is tuned on the basis of the Modulus Optimum method (MO-m). The basic speed controllers are tuned by the Extended Symmetrical Optimum method (ESO-m) and the developed continuous-time speed controllers are discretized using Tustin's method. The developed speed controllers are: (1) a classical PI controller, (2) a Takagi-Sugeno PI fuzzy controllers (TS-PI-FCs), (3) a two-degree-of-freedom PID (2-DOF PID) and (4) a sliding mode (SM) PI quasi relay control solution. The cost-effective feature is ensured by simple controller design and easy implementation, and it is illustrated by a case study which includes simulation results. A process with variable inertia, variable reference and load disturbance is discussed due to its applicability as a controlled plant in the field of mechatronic systems.

关键词： Mechatronic systems PI controllers fuzzy controllers two-degree-of-freedom controllers sliding mode controllers variable parameters

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Agile online-trained neural network models by using Robust Fixed Point Transformations

Agile online-trained neural network models by using Robust F...

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IEEE International Symposium on Intelligent Signal Processing

作者： Teréz A. Várkonyi Vincenzo Piuri József K. Tar Annamária R. Várkonyi-Kóczy Imre J. Rudas John von Neumann Faculty of Informatics Obuda University Budapest Hungary Department of Computer Science Universitá degli Studi di Milano Crema Italy Institute of Applied Mathematics John von Neumann Faculty of Informatics Obuda University Budapest Hungary Donát Bánki Faculty of Mechanical and Safety Engineering Obuda University Budapest Hungary

Nowadays, in the field of information processing, neural networks (NNs) are very used, because they can learn adaptively how to behave in a desired way. In the field of adaptive control, NNs are the most beneficial when the system to be controlled is not known in advance, because the system can be modeled by NNs to predict its behavior. In this case, it is very important how accurate the estimation of the NN is, since if the approximation is too rough then extra calculations are needed to get better results. One of the possibilities for improving the NN model is on-line learning during the control process, but this option requires high computational time. Another possibility is the application of Robust Fixed Point Transformations (RFPT), since though, it can only guarantee local stability, RFPT has been developed to reduce the inaccuracy caused by modeling errors and it does not need high computational time. In this paper, a new combination of the two methods the on-line trained neural networks and RFPT is proposed to decrease the computational burden caused by the on-line adaptation and keep the results close to optimum.

关键词： Artificial neural networks Approximation methods Training Adaptation models Robustness Computational modeling

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Advanced Communication System for Rich and Green Smart Grid Networking

Advanced Communication System for Rich and Green Smart Grid ...

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IEEE PES Innovative Smart Grid Technologies Conference

作者： Helber Silva Augusto Neto Eduardo Cerqueira Felipe Dantas Hugo Barros Everton Almeida Department of Informatics Federal Institute of Rio Grande do Norte Brazil Department of Informatics Engineering (DETI) Federal University of Ceara Brazil Computer Engineering (ENGCOMP) Federal University of Para Brazil Department of Informatics and Applied Mathematics (DIMAp) Federal University of Rio Grande do Norte Brazil

ISBN: (纸本)9781467352727

Future Green Smart Grids are expected to support sustainable, safe, robust, efficient and intelligent production, distribution and consumption of electric energy. However, evolving immaturity and issues restrict their development, confronting interoperability and reducing the reliability of the power grid. Innovating networking capabilities are of paramount to provide rich Smart Grid networking, while keeping the system performance in large scale scenarios. In view of this, we designed the Session-Oriented Communication System (SOCSys) solution for dependable IP-based Smart Grid networking over a wireless mesh QoS-aware information network. In this paper, we propose the Advanced SOCSys (ASOCSys), extending our previous work with network-centric functionalities. ASOCSys aims at improving IP-based Smart Grid networking through group-based session admission control and rich networking IEEE 802.16 compliant information network. Simulation results show that ASOCSys outperforms standards currently considered for Smart Grids, in terms of throughput, latency and propagation delay, while consuming low network resources.

关键词： Smart Grid networking Quality of Service dependable wireless communications Group-based driven admission control

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A Novel SPECT Reconstruction Algorithm with Fast Convergence Rate

A Novel SPECT Reconstruction Algorithm with Fast Convergence...

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2013 International Conference on Biological,Medical and Chemical engineering(BMCE 2013)

作者： Ruei-Huang YU Shyh-Hau WANG Shiang-Bin JONG Yu-Chang TYAN Cheng-Lien LANG Ying-Fong HUANG Department of Computer Science and Information Engineering & Institute of Medical Informatics National Cheng Kung University Department of Medical Imaging and Radiological Sciences Kaohsiung Medical University Department of Nuclear Medicine Kaohsiung Medical University Chung-Ho Memorial Hospital National Sun Yat-Sen University-Kaohsiung Medical University Joint Research Center Department of Applied Mathematics I-SHOU University

In this paper,a novel algorithm with fast convergence rate has been accomplished to increase the efficiency of maximum likelihood expectation maximization(MLEM)and ordered subsets expectation maximization(OSEM).This algorithm began with the input of the sinogram image collected from a single photon emission computed tomography(SPECT)*** procedure of orthogonal cross reference(OCR)image formation then *** order to produce a better OCR image,the region of interest(ROI)of the sinogram image with maximum detection amount was automatic ***,the probability matrix was reduced according to the OCR ***,an initial estimated image with all pixel values are 1s was input to iteratively reconstruct using MLEM and OSEM with the reduced probability *** showed that obvious improvements of convergence rate and quality could be obtained and a lot of computational time could be ***,the effect of image blurring could be efficiently restrained by using *** novel algorithm is then capable of being put to use in clinical applications to further increase the accuracy of clinical diagnosis and the efficiency of clinical image reconstruction.

关键词： MLEM OSEM SPECT OCR ROI

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A survey of management interfaces for eucalyptus cloud

A survey of management interfaces for eucalyptus cloud

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7th IEEE International Symposium on applied Computational Intelligence and informatics, SACI 2012

作者： Lonea, A.M. Popescu, D.E. Prostean, O. Politehnica University of Timisoara Automation and Applied Informatics Department Timisoara Romania University of Oradea Computer Engineering Department Oradea Romania

ISBN: (纸本)9781467310116

Cloud Computing is a technology which is susceptible to a continuous development, because of its strong advantages of accessing data from any place in the world over the Internet without concerning about the infrastructure used and the problems involved by the installation and maintenance processes. The purpose of this article is to provide an overview of several management interfaces for Eucalyptus cloud by addressing the taxonomy and evaluation of the cloud management interfaces. The taxonomy proposed in this paper results from the work accomplished by experimenting the Eucalyptus community cloud. First, an evaluation of the Eucalyptus architecture is presented, in order to emphasize the Eucalyptus platform involved in cloud management process, which facilitates the deployment, management and execution of Infrastructure-as-a-Service (IaaS). The cloud management tools are described from two perspectives. The first perspective analyzes the cloud portals from the user roles, while the second perspective addresses them with respect to the type of the tools employed. The taxonomy presented in this paper is related with the 5 elements of the Common Cloud Management Architecture (CCMA), which was provided by Behrendt, et al. (2011) as one of the components of IBM Cloud Computing Reference Architecture. Thus, the first category of interfaces (i.e. the cloud portals from the user roles) encompasses the Service Consumer Portal, the Service Provider Portal and the Service Development Portal, while second category of interfaces includes the main components of CCMA: Operational Support Services (OSS) and Business Support Services (BSS). Cloud management is a subject approached by researchers in the community and this can be observed by the big number of third party cloud management providers (i.e. RightScale, enStratus, IMOD Kaavo, CloudWatch, Scarl, Tapin, Cloudkick). This article is motivated by the fact that cloud management is a fundamental support for all users of cloud s

关键词： Taxonomies

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A Brief Introduction to Classification for Smart Grid

A Brief Introduction to Classification for Smart Grid

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IEEE International Conference on Systems, Man, and Cybernetics

作者： Chun-Wei Tsai Alexander Pelov Ming-Chao Chiang Chu-Sing Yang Tzung-Pei Hong Department of Applied Informatics and Multimedia Chia Nan University of Pharmacy & Science Tainan 71710 Taiwan R.O.C. Networks Security and Multimedia TELECOM Bretagne Cesson-Sévigné France Department of Computer Science and Engineering National Sun Yat-sen University Kaohsiung 80424 Taiwan R.O.C. Department of Electrical Engineering National Cheng Kung University Tainan 70101 Taiwan R.O.C. Department of Computer Science and Information Engineering National University of Kaohsiung Kaohsiung 81148 Taiwan R.O.C.

ISBN: (纸本)9781479906505

There is no doubt about the potentials of smart grid, for the traditional power grid has been kind of out of date, in terms of not only its infrastructure but also its restrictions on the way information is communicated. To provide better and smarter services via smart grid, the first thing we have to do is to make it more intelligent. Among the technologies that can be applied to smart grid to make it more intelligent, data mining will certainly play a vital role. This paper begins with a brief introduction to smart grid, followed by a discussion on the supervised learning (classification) and the unsupervised learning (clustering). Several open and possible research issues are then given to depict the future trends of smart grid.

关键词： Smart grid data mining and machine learning Smart grids data mining Power grids Unsupervised learning

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Combined Measurement of the Higgs Boson Mass in pp Collisions at s=7 and 8 TeV with the ATLAS and CMS Experiments

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Physical Review Letters 2015年第19期114卷 191803-191803页

作者： G. Aad B. Abbott J. Abdallah O. Abdinov R. Aben M. Abolins O. S. AbouZeid H. Abramowicz H. Abreu R. Abreu Y. Abulaiti B. S. Acharya L. Adamczyk D. L. Adams J. Adelman S. Adomeit T. Adye A. A. Affolder T. Agatonovic-Jovin J. A. Aguilar-Saavedra S. P. Ahlen F. Ahmadov G. Aielli H. Akerstedt T. P. A. Åkesson G. Akimoto A. V. Akimov G. L. Alberghi J. Albert S. Albrand M. J. Alconada Verzini M. Aleksa I. N. Aleksandrov C. Alexa G. Alexander T. Alexopoulos M. Alhroob G. Alimonti L. Alio J. Alison S. P. Alkire B. M. M. Allbrooke P. P. Allport A. Aloisio A. Alonso F. Alonso C. Alpigiani A. Altheimer B. Alvarez Gonzalez D. Álvarez Piqueras M. G. Alviggi B. T. Amadio K. Amako Y. Amaral Coutinho C. Amelung D. Amidei S. P. Amor Dos Santos A. Amorim S. Amoroso N. Amram G. Amundsen C. Anastopoulos L. S. Ancu N. Andari T. Andeen C. F. Anders G. Anders J. K. Anders K. J. Anderson A. Andreazza V. Andrei S. Angelidakis I. Angelozzi P. Anger A. Angerami F. Anghinolfi A. V. Anisenkov N. Anjos A. Annovi M. Antonelli A. Antonov J. Antos F. Anulli M. Aoki L. Aperio Bella G. Arabidze Y. Arai J. P. Araque A. T. H. Arce F. A. Arduh J-F. Arguin S. Argyropoulos M. Arik A. J. Armbruster O. Arnaez V. Arnal H. Arnold M. Arratia O. Arslan A. Artamonov G. Artoni S. Asai N. Asbah A. Ashkenazi B. Åsman L. Asquith K. Assamagan R. Astalos M. Atkinson N. B. Atlay B. Auerbach K. Augsten M. Aurousseau G. Avolio B. Axen M. K. Ayoub G. Azuelos M. A. Baak A. E. Baas C. Bacci H. Bachacou K. Bachas M. Backes M. Backhaus E. Badescu P. Bagiacchi P. Bagnaia Y. Bai T. Bain J. T. Baines O. K. Baker P. Balek T. Balestri F. Balli E. Banas Sw. Banerjee A. A. E. Bannoura H. S. Bansil L. Barak S. P. Baranov E. L. Barberio D. Barberis M. Barbero T. Barillari M. Barisonzi T. Barklow N. Barlow S. L. Barnes B. M. Barnett R. M. Barnett Z. Barnovska A. Baroncelli G. Barone A. J. Barr F. Barreiro J. Barreiro Guimarães da Costa R. Bartoldus A. E. Barton P. Bartos A. Bassalat A. Basye R. L. Bates S. J. Batista J. R. Batley M. Battaglia M. Bauce F. Bauer H. S. Bawa J. B. Beach CPPM Aix-Marseille Université and CNRS/IN2P3 Marseille France Homer L. Dodge Department of Physics and Astronomy University of Oklahoma Norman Oklahoma USA Institute of Physics Academia Sinica Taipei Taiwan Institute of Physics Azerbaijan Academy of Sciences Baku Azerbaijan Nikhef National Institute for Subatomic Physics and University of Amsterdam Amsterdam Netherlands Department of Physics and Astronomy Michigan State University East Lansing Michigan USA Department of Physics University of Toronto Toronto Ontario Canada Raymond and Beverly Sackler School of Physics and Astronomy Tel Aviv University Tel Aviv Israel Department of Physics Technion: Israel Institute of Technology Haifa Israel CERN Geneva Switzerland Department of Physics Stockholm University Sweden The Oskar Klein Centre Stockholm Sweden INFN Gruppo Collegato di Udine Sezione di Trieste Udine Italy ICTP Trieste Italy AGH University of Science and Technology Faculty of Physics and Applied Computer Science Krakow Poland Physics Department Brookhaven National Laboratory Upton New York USA Department of Physics Northern Illinois University DeKalb Illinois USA Fakultät für Physik Ludwig-Maximilians-Universität München München Germany Particle Physics Department Rutherford Appleton Laboratory Didcot United Kingdom Oliver Lodge Laboratory University of Liverpool Liverpool United Kingdom Institute of Physics University of Belgrade Belgrade Serbia Laboratorio de Instrumentacao e Fisica Experimental de Particulas-LIP Lisboa Portugal Departamento de Fisica Teorica y del Cosmos and CAFPE Universidad de Granada Granada (Spain) Portugal Department of Physics Boston University Boston Massachusetts USA Joint Institute for Nuclear Research JINR Dubna Dubna Russia INFN Sezione di Roma Tor Vergata Roma Italy Dipartimento di Fisica Università di Roma Tor Vergata Roma Italy Fysiska institutionen Lunds universitet Lund Sweden International Center for Elementary Particle Physics and Depart

A measurement of the Higgs boson mass is presented based on the combined data samples of the ATLAS and CMS experiments at the CERN LHC in the H→γγ and H→ZZ→4ℓ decay channels. The results are obtained from a simultaneous fit to the reconstructed invariant mass peaks in the two channels and for the two experiments. The measured masses from the individual channels and the two experiments are found to be consistent among themselves. The combined measured mass of the Higgs boson is mH=125.09±0.21 (stat)±0.11 (syst) GeV.

关键词： HIGGS bosons RESEARCH COLLISIONS (Nuclear physics) ATLAS (computer program language) REST mass (Relativity) BOSONS

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