检索结果-内蒙古大学图书馆

Search for Dark Matter Produced in Association with a Higgs Boson Decaying to bb¯ Using 36 fb−1 of pp Collisions at s=13 TeV with the ATLAS Detector

引用

Physical Review Letters 2017年第18期119卷 181804-181804页

作者： M. Aaboud G. Aad B. Abbott O. Abdinov B. Abeloos S. H. Abidi O. S. AbouZeid N. L. Abraham H. Abramowicz H. Abreu R. Abreu Y. Abulaiti B. S. Acharya S. Adachi L. Adamczyk J. Adelman M. Adersberger T. Adye A. A. Affolder T. Agatonovic-Jovin C. Agheorghiesei J. A. Aguilar-Saavedra S. P. Ahlen F. Ahmadov G. Aielli S. Akatsuka H. Akerstedt T. P. A. Åkesson E. Akilli A. V. Akimov G. L. Alberghi J. Albert P. Albicocco M. J. Alconada Verzini S. C. Alderweireldt M. Aleksa I. N. Aleksandrov C. Alexa G. Alexander T. Alexopoulos M. Alhroob B. Ali M. Aliev G. Alimonti J. Alison S. P. Alkire B. M. M. Allbrooke B. W. Allen P. P. Allport A. Aloisio A. Alonso F. Alonso C. Alpigiani A. A. Alshehri M. I. Alstaty B. Alvarez Gonzalez D. Álvarez Piqueras M. G. Alviggi B. T. Amadio Y. Amaral Coutinho C. Amelung D. Amidei S. P. Amor Dos Santos A. Amorim S. Amoroso G. Amundsen C. Anastopoulos L. S. Ancu N. Andari T. Andeen C. F. Anders J. K. Anders K. J. Anderson A. Andreazza V. Andrei S. Angelidakis I. Angelozzi A. Angerami A. V. Anisenkov N. Anjos A. Annovi C. Antel M. Antonelli A. Antonov D. J. Antrim F. Anulli M. Aoki L. Aperio Bella G. Arabidze Y. Arai J. P. Araque V. Araujo Ferraz A. T. H. Arce R. E. Ardell F. A. Arduh J-F. Arguin S. Argyropoulos M. Arik A. J. Armbruster L. J. Armitage O. Arnaez H. Arnold M. Arratia O. Arslan A. Artamonov G. Artoni S. Artz S. Asai N. Asbah A. Ashkenazi L. Asquith K. Assamagan R. Astalos M. Atkinson N. B. Atlay K. Augsten G. Avolio B. Axen M. K. Ayoub G. Azuelos A. E. Baas M. J. Baca H. Bachacou K. Bachas M. Backes M. Backhaus P. Bagnaia M. Bahmani H. Bahrasemani J. T. Baines M. Bajic O. K. Baker E. M. Baldin P. Balek F. Balli W. K. Balunas E. Banas A. Bandyopadhyay Sw. Banerjee A. A. E. Bannoura L. Barak E. L. Barberio D. Barberis M. Barbero T. Barillari M-S Barisits J. T. Barkeloo T. Barklow N. Barlow S. L. Barnes B. M. Barnett R. M. Barnett Z. Barnovska-Blenessy A. Baroncelli G. Barone A. J. Barr L. Barranco Navarro F. Barreiro J. Barreiro Guimarães da Costa R. Bartoldus A. E. Barton P. Bartos A. Faculté des Sciences Université Mohamed Premier and LPTPM Oujda Morocco 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 Azerbaijan Academy of Sciences Baku Azerbaijan LAL Univ. Paris-Sud CNRS/IN2P3 Université Paris-Saclay Orsay France Department of Physics University of Toronto Toronto Ontario Canada Santa Cruz Institute for Particle Physics University of California Santa Cruz Santa Cruz California USA Department of Physics and Astronomy University of Sussex Brighton United Kingdom 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 Center for High Energy Physics University of Oregon Eugene Oregon USA 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 International Center for Elementary Particle Physics and Department of Physics The University of Tokyo Tokyo Japan AGH University of Science and Technology Faculty of Physics and Applied Computer Science Krakow Poland 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 Institute of Physics University of Belgrade Belgrade Serbia Department of Physics Alexandru Ioan Cuza University of Iasi Iasi Romania Laboratório de Instrumentação e Física Experimental de Partículas - LIP Lisboa Portugal Departamento de Fisica Teorica y del Cosmos and CAFPE Universidad de Granada Granada Portugal Department of Physics Boston University Boston Massachusetts USA Joint Institute for Nuclear Research JINR Dubna Dubna Russia INFN Sezione di Roma Tor Vergata Italy Dipartimen

Several extensions of the standard model predict associated production of dark-matter particles with a Higgs boson. Such processes are searched for in final states with missing transverse momentum and a Higgs boson decaying to a bb¯ pair with the ATLAS detector using 36.1 fb−1 of pp collisions at a center-of-mass energy of 13 TeV at the LHC. The observed data are in agreement with the standard model predictions and limits are placed on the associated production of dark-matter particles and a Higgs boson.

关键词： Extensions of Higgs sector Particle dark matter Weakly interacting massive particles

来源：评论

学校读者我要写书评

暂无评论

parallel Bayesian Network Structure Learning for Genome-Scale Gene Networks

Parallel Bayesian Network Structure Learning for Genome-Scal...

引用

Supercomputing Conference

作者： Sanchit Misra Md. Vasimuddin Kiran Pamnany Sriram P. Chockalingam Yong Dong Min Xie Maneesha R. Aluru Srinivas Aluru Parallel Computing Lab Intel Corporation Bangalore India Dept. of Computer Science and Engineering Indian Institute of Technology Bombay Mumbai India State Key Laboratory of High Performance Computing National University of Defense Technology Changsha China School of Biology Georgia Institute of Technology Atlanta USA School of Computational Science and Engineering Georgia Institute of Technology Atlanta USA

Learning Bayesian networks is NP-hard. Even with recent progress in heuristic and parallel algorithms, modeling capabilities still fall short of the scale of the problems encountered. In this paper, we present a massively parallel method for Bayesian network structure learning, and demonstrate its capability by constructing genome-scale gene networks of the model plant Arabidopsis thaliana from over 168.5 million gene expression values. We report strong scaling efficiency of 75% and demonstrate scaling to 1.57 million cores of the Tianhe-2 supercomputer. Our results constitute three and five orders of magnitude increase over previously published results in the scale of data analyzed and computations performed, respectively. We achieve this through algorithmic innovations, using efficient techniques to distribute work across all compute nodes, all available processors and coprocessors on each node, all available threads on each processor and coprocessor, and vectorization techniques to maximize single thread performance.

关键词： Bayes methods Hypercubes Instruction sets Genomics Bioinformatics Coprocessors Vectors

来源：评论

学校读者我要写书评

暂无评论

Correction to: Identification and rejection of pile-up jets at high pseudorapidity with the ATLAS detector

引用

The European Physical Journal C 2017年第10期77卷 1-14页

作者： Aaboud, M. Aad, G. Abbott, B. Abdallah, J. Abdinov, O. Abeloos, B. Abidi, S. H. AbouZeid, O. S. Abraham, N. L. Abramowicz, H. Abreu, H. Abreu, R. Abulaiti, Y. Acharya, B. S. Adachi, S. Adamczyk, L. Adelman, J. Adersberger, M. Adye, T. Affolder, A. A. Agatonovic-Jovin, T. Agheorghiesei, C. Aguilar-Saavedra, J. A. Ahlen, S. P. Ahmadov, F. Aielli, G. Akatsuka, S. Akerstedt, H. Åkesson, T. P. A. Akilli, E. Akimov, A. V. Alberghi, G. L. Albert, J. Albicocco, P. Verzini, M. J. Alconada Aleksa, M. Aleksandrov, I. N. Alexa, C. Alexander, G. Alexopoulos, T. Alhroob, M. Ali, B. Aliev, M. Alimonti, G. Alison, J. Alkire, S. P. Allbrooke, B. M. M. Allen, B. W. Allport, P. P. Aloisio, A. Alonso, A. Alonso, F. Alpigiani, C. Alshehri, A. A. Alstaty, M. Gonzalez, B. Alvarez Piqueras, D. Álvarez Alviggi, M. G. Amadio, B. T. Coutinho, Y. Amaral Amelung, C. Amidei, D. Santos, S. P. Amor Dos Amorim, A. Amoroso, S. Amundsen, G. Anastopoulos, C. Ancu, L. S. Andari, N. Andeen, T. Anders, C. F. Anders, J. K. Anderson, K. J. Andreazza, A. Andrei, V. Angelidakis, S. Angelozzi, I. Angerami, A. Anisenkov, A. V. Anjos, N. Annovi, A. Antel, C. Antonelli, M. Antonov, A. Antrim, D. J. Anulli, F. Aoki, M. Bella, L. Aperio Arabidze, G. Arai, Y. Araque, J. P. Ferraz, V. Araujo Arce, A. T. H. Ardell, R. E. Arduh, F. A. Arguin, J.-F. Argyropoulos, S. Arik, M. Armbruster, A. J. Armitage, L. J. Arnaez, O. Arnold, H. Arratia, M. Arslan, O. Artamonov, A. Artoni, G. Artz, S. Asai, S. Asbah, N. Ashkenazi, A. Asquith, L. Assamagan, K. Astalos, R. Atkinson, M. Atlay, N. B. Augsten, K. Avolio, G. Axen, B. Ayoub, M. K. Azuelos, G. Baas, A. E. Baca, M. J. Bachacou, H. Bachas, K. Backes, M. Backhaus, M. Bagnaia, P. Bahrasemani, H. Baines, J. T. Bajic, M. Baker, O. K. Baldin, E. M. Balek, P. Balli, F. Balunas, W. K. Banas, E. Banerjee, Sw. Bannoura, A. A. E. Barak, L. Barberio, E. L. Barberis, D. Barbero, M. Barillari, T. Barisits, M.-S. Barklow, T. Barlow, N. Barnes, S. L. Barnett, B. M. Barnett, R. M. Barnovska-Blenessy, Z. Baroncelli, A. Barone, G. Barr, A. J. Faculté des Sciences Université Mohamed Premier and LPTPM Oujda Morocco CPPM Aix-Marseille Université and CNRS/IN2P3 Marseille France Homer L. Dodge Department of Physics and Astronomy University of Oklahoma Norman USA Department of Physics The University of Texas at Arlington Arlington USA Department of Physics University of Adelaide Adelaide Australia Institute of Physics Azerbaijan Academy of Sciences Baku Azerbaijan LAL Univ. Paris-Sud CNRS/IN2P3 Université Paris-Saclay Orsay France Department of Physics University of Toronto Toronto Canada Santa Cruz Institute for Particle Physics University of California Santa Cruz Santa Cruz USA Department of Physics and Astronomy University of Sussex Brighton UK 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 Center for High Energy Physics University of Oregon Eugene USA Department of Physics Stockholm University Stockholm Sweden The Oskar Klein Centre Stockholm Sweden INFN Gruppo Collegato di Udine Sezione di Trieste Udine Italy ICTP Trieste Italy International Center for Elementary Particle Physics and Department of Physics The University of Tokyo Tokyo Japan Faculty of Physics and Applied Computer Science AGH University of Science and Technology Kraków Poland Department of Physics Northern Illinois University DeKalb USA Fakultät für Physik Ludwig-Maximilians-Universität München Munich Germany Particle Physics Department Rutherford Appleton Laboratory Didcot UK Institute of Physics University of Belgrade Belgrade Serbia Department of Physics Alexandru Ioan Cuza University of Iasi Iasi Romania Laboratório de Instrumentação e Física Experimental de Partículas-LIP Lisbon Portugal Departamento de Fisica Teorica y del Cosmos and CAFPE Universidad de Granada Granada Spain Department of Physics Boston University Boston USA Joint Institute for Nuclear Research JINR Dubna Dubn

Unfortunately, in the original version of this article the copyright holder was wrong in the HTML. The original article has been corrected.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Spatial indexing in agent-based crowd simulation 6

Spatial indexing in agent-based crowd simulation

引用

6th International Conference on Simulation Tools and Techniques, SIMUTools 2013

作者： Othman, Nasri Bin Luo, Linbo Cai, Wentong Lees, Michael Parallel and Distributed Computing Centre School of Computer Engineering Nanyang Technological University Singapore639798 Singapore

ISBN: (纸本)9781936968763

Crowd modeling and simulation has become a critical tool for understanding crowds and predicting their behaviours. This is accomplished by modelling the characteristics and behaviours of large groups of people, as well as their interactions. Agent-based crowd simulation may involve thousands of complex agents interacting in sophisticated ways, in close spatial proximity, with each other. A key challenge to the development of agent-based crowd simulation is the inherent complexity that is required to model all its necessary elements. A necessary feature of such a simulation is spatial indexing. This refers to the use of data structures to organize collections of simulation entities (e.g., agents and obstacles) in a manner which allows for efficient spatial querying. This is especially pertinent for large-scale crowd simulation with agents that sense their surrounding environment periodically, as the cost of spatial querying becomes computationally expensive if done naively. In this paper, we will describe our experience in improving the existing grid-based spatial indexing approach in our agent-based crowd simulation. Also, we will explore the integration of the adaptive spatial indices (e.g., R-tree and quad-tree) into our system. The performances of various spatial indexing techniques are examined in terms of efficiency and scalability. Copyright © 2013 ICST.

关键词： Decision trees

来源：评论

学校读者我要写书评

暂无评论

Towards a framework for adaptive resource provisioning in large-scale distributed agent-based simulation

Towards a framework for adaptive resource provisioning in la...

引用

Lecture Notes in computer science

作者： Hanai, Masatoshi Suzumura, Toyotaro Ventresque, Anthony Shudo, Kazuyuki Tokyo Institute of Technology Dept. of Mathematical and Computing Sciences 2-12-1 Ookayama MeguroTokyo152-8552 Japan School of Computer Science and Informatics University College Dublin Ireland Lero The Irish Software Engineering Research Centre Damastown Industrial Estate Mulhuddart Dublin 15 Ireland Smarter Cities Technology Centre IBM Research Damastown Industrial Estate Mulhuddart Dublin 15 Ireland

ISBN: (纸本)9783319143248

Large scale distributed agent-based simulations run on several computing units (e.g., virtual machines in the Cloud, nodes in a supercomputer). Classically, these systems try to (re-)load-balance the nodes as overloaded nodes slow down the *** another challenge in large scale distributed simulations is that the overall load evolves. In this paper we leverage on commodity computing to adapt resource provisioning (number of computing units) to the load during the execution of the simulation. We also propose an asynchronous migration mechanism that migrate workload between computing nodes efficiently when nodes wait for synchronisation barriers to happen. We validate our implementation on a scenario simulating one day of vehicular traffic in Tokyo, running on 2 to 8 machines depending on the demand. Our evaluation shows a 26% reduction in data migration time compared to a naive migration approach between computing units. © Springer International Publishing Switzerland 2014.

关键词： Supercomputers

来源：评论

学校读者我要写书评

暂无评论

Cloudsme: Developing a cloud computing-based platform for simulation in manufacturing and engineering

Cloudsme: Developing a cloud computing-based platform for si...

引用

2014 Operational Research Society Simulation Workshop, SW 2014

作者： Taylor, Simon J. E. Kiss, Tamas Kacsuk, Peter Terstyanszky, Gabor Nicola, Fantini Department of Information Systems and Computing Brunel University Uxbridge MiddlesexUB8 3PH United Kingdom Centre for Parallel Computing Department of Business Information Systems University of Westminster 115 New Cavendish St LondonW1W 6UW United Kingdom MTA SZTAKI Victor Hugo u. 18-22 Budapest1132 Hungary Department of Computer Science and Software Engineering Faculty of Science and Technology University of Westminster LondonW1W 6UW United Kingdom Huobstrasse 10 Pfäffikon8808 Switzerland

There is a demand from simulation users for speed, the ability to obtain quickly results from simulation runs. Cloud computing offers the potential for scalable, on-demand access to resources that can be used to speed up simulation. However, developing cloud computing solutions for industry is difficult without appropriate expertise. This paper introduces the CloudSME project that is dedicated to developing cloud computing solutions for simulation in industry and presents an overview of the CloudSME Simulation Platform that is being used to support an initial set of Cloud-based versions of Simul8's discrete-event simulation environment, Ascomp's TransAT computational fluid dynamics application, Ingecon's 3D Scan Insole Designer tool and 2MORO's Bfly software for aircraft maintenance logistics. The paper presents an overview of cloud computing, the CloudSME project, the architecture of the CloudSME Simulation Platform and its two key elements: gUse and CloudBroker.

关键词： Discrete event simulation

来源：评论

学校读者我要写书评

暂无评论

A hybrid floor identification algorithm based on Bayesian classification and special AP

A hybrid floor identification algorithm based on Bayesian cl...

引用

International Conference on Information and Automation (ICIA)

作者： Fang Zhao Dan Luo Wu Yuan Haiyong Luo School of Software Engineering International School Beijing University of Posts and Telecommunications Beijing China NSFC Taiyuan-Zhongguancun Cooperation School of Computer Science Beijing Institute of Technology Beijing China Research Centre of Pervasive Computing Institute of Computing Technology Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781479940998

Accurately discriminating different floors is a very important task in indoor fingerprinting localization, which can be used to reduce space search domain and improve localization accuracy. There exist some research works for floor identification at present; however, the accuracy is not high. To achieve higher accuracy, this paper proposes a hybrid floor identification algorithm using Bayesian classification and special AP. By extracting the distribution feature of APs in different floors with training data, the proposed approach can determine floor efficiently with 100% accuracy.

关键词： Floors IEEE 802.11 Standards Bayes methods Accuracy Classification algorithms Training

来源：评论

学校读者我要写书评

暂无评论

Interactive scenario generation for mission-based virtual training

Interactive scenario generation for mission-based virtual tr...

引用

作者： Luo, Linbo Yin, Haiyan Cai, Wentong Lees, Michael Zhou, Suiping Parallel and Distributed Computing Centre School of Computer Engineering Nanyang Technological University Singapore Singapore School of Computing Teesside University Middlesbrough United Kingdom

For a virtual training system, how to effectively and quickly generate training scenarios has become a challenging issue. A scenario generation system is needed to produce scenarios that can meet different objectives and at the same time be customized for individuals. In this paper, we introduce a scenario generation framework for mission-based virtual training, which aims to generate scenarios from both trainer and trainee's perspective. The framework allows a trainer to direct the scenario generation process, so that the generated scenarios reflect the trainer's preferences over different mission objectives. It also considers how the scenarios could adapt to different trainees' skill levels. The representation of scenario beat is proposed, and the scenario generation process adopts a combinatorial optimization approach generating the sequence of scenario beats. The efficacy of the proposed framework is demonstrated through an empirical study of human players in a simple food distribution mission game. The results show that a trainee can achieve better performance improvement when playing the customized scenarios tailored to the trainee's skill level as compared with the uncustomized scenarios. Copyright © 2013 John Wiley & Sons, Ltd.

关键词： Combinatorial optimization

来源：评论

学校读者我要写书评

暂无评论

Search for squarks and gluinos in events with an isolated lepton, jets, and missing transverse momentum at s=13 TeV with the ATLAS detector

引用

Physical Review D 2017年第11期96卷 112010-112010页

作者： M. Aaboud G. Aad B. Abbott O. Abdinov B. Abeloos S. H. Abidi O. S. AbouZeid N. L. Abraham H. Abramowicz H. Abreu R. Abreu Y. Abulaiti B. S. Acharya S. Adachi L. Adamczyk J. Adelman M. Adersberger T. Adye A. A. Affolder T. Agatonovic-Jovin C. Agheorghiesei J. A. Aguilar-Saavedra S. P. Ahlen F. Ahmadov G. Aielli S. Akatsuka H. Akerstedt T. P. A. Åkesson E. Akilli A. V. Akimov G. L. Alberghi J. Albert P. Albicocco M. J. Alconada Verzini S. C. Alderweireldt M. Aleksa I. N. Aleksandrov C. Alexa G. Alexander T. Alexopoulos M. Alhroob B. Ali M. Aliev G. Alimonti J. Alison S. P. Alkire B. M. M. Allbrooke B. W. Allen P. P. Allport A. Aloisio A. Alonso F. Alonso C. Alpigiani A. A. Alshehri M. I. Alstaty B. Alvarez Gonzalez D. Álvarez Piqueras M. G. Alviggi B. T. Amadio Y. Amaral Coutinho C. Amelung D. Amidei S. P. Amor Dos Santos A. Amorim S. Amoroso G. Amundsen C. Anastopoulos L. S. Ancu N. Andari T. Andeen C. F. Anders J. K. Anders K. J. Anderson A. Andreazza V. Andrei S. Angelidakis I. Angelozzi A. Angerami A. V. Anisenkov N. Anjos A. Annovi C. Antel M. Antonelli A. Antonov D. J. Antrim F. Anulli M. Aoki L. Aperio Bella G. Arabidze Y. Arai J. P. Araque V. Araujo Ferraz A. T. H. Arce R. E. Ardell F. A. Arduh J-F. Arguin S. Argyropoulos M. Arik A. J. Armbruster L. J. Armitage O. Arnaez H. Arnold M. Arratia O. Arslan A. Artamonov G. Artoni S. Artz S. Asai N. Asbah A. Ashkenazi L. Asquith K. Assamagan R. Astalos M. Atkinson N. B. Atlay K. Augsten G. Avolio B. Axen M. K. Ayoub G. Azuelos A. E. Baas M. J. Baca H. Bachacou K. Bachas M. Backes M. Backhaus P. Bagnaia M. Bahmani H. Bahrasemani J. T. Baines M. Bajic O. K. Baker E. M. Baldin P. Balek F. Balli W. K. Balunas E. Banas A. Bandyopadhyay Sw. Banerjee A. A. E. Bannoura L. Barak E. L. Barberio D. Barberis M. Barbero T. Barillari M-S Barisits J. T. Barkeloo T. Barklow N. Barlow S. L. Barnes B. M. Barnett R. M. Barnett Z. Barnovska-Blenessy A. Baroncelli G. Barone A. J. Barr L. Barranco Navarro F. Barreiro J. Barreiro Guimarães da Costa R. Bartoldus A. E. Barton P. Bartos A. Faculté des Sciences Université Mohamed Premier and LPTPM Oujda Morocco 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 Azerbaijan Academy of Sciences Baku Azerbaijan LAL Univ. Paris-Sud CNRS/IN2P3 Université Paris-Saclay Orsay France Department of Physics University of Toronto Toronto ON Canada Santa Cruz Institute for Particle Physics University of California Santa Cruz Santa Cruz California USA Department of Physics and Astronomy University of Sussex Brighton United Kingdom 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 Center for High Energy Physics University of Oregon Eugene Oregon USA Department of Physics Stockholm University Stockholm Sweden The Oskar Klein Centre Stockholm Sweden INFN Gruppo Collegato di Udine Sezione di Trieste Udine Italy ICTP Trieste Italy International Center for Elementary Particle Physics and Department of Physics The University of Tokyo Tokyo Japan AGH University of Science and Technology Faculty of Physics and Applied Computer Science Krakow Poland 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 Institute of Physics University of Belgrade Belgrade Serbia Department of Physics Alexandru Ioan Cuza University of Iasi Iasi Romania Laboratório de Instrumentação e Física Experimental de Partículas - LIP Lisboa Portugal Departamento de Fisica Teorica y del Cosmos Universidad de Granada Granada Portugal Department of Physics Boston University Boston Massachusetts USA Joint Institute for Nuclear Research JINR Dubna Dubna Russia INFN Sezione di Roma Tor Vergata Italy Dipartimento di

The results of a search for squarks and gluinos in final states with an isolated electron or muon, multiple jets and large missing transverse momentum using proton-proton collision data at a center-of-mass energy of s=13 TeV are presented. The data set used was recorded during 2015 and 2016 by the ATLAS experiment at the Large Hadron Collider and corresponds to an integrated luminosity of 36.1 fb−1. No significant excess beyond the expected background is found. Exclusion limits at 95% confidence level are set in a number of supersymmetric scenarios, reaching masses up to 2.1 TeV for gluino pair production and up to 1.25 TeV for squark pair production.

关键词： Supersymmetry Particle data analysis

来源：评论

学校读者我要写书评

暂无评论

Performance of the ATLAS track reconstruction algorithms in dense environments in LHC Run 2

引用

EUROPEAN PHYSICAL JOURNAL C 2017年第10期77卷 1页

作者： Aaboudd, M. Aad, G. Abbott, B. Abdallah, J. Abdinov, O. Abeloos, B. Abidi, S. H. AbouZeid, O. S. Abraham, N. L. Abramowicz, H. Abreu, H. Abreu, R. Abulaitia, Y. Acharya, B. Adachi, S. Adamczyk, L. Adelman, J. Adersberger, M. Adye, T. Affolder, A. A. Agatonovic-Jovin, T. Agheorghiesei, C. Aguilar-Saavedra, J. A. Ahlen, S. P. Ahmadov, F. Aielli, G. Akatsuka, S. Akerstedt, H. Akesson, T. P. Akimov, A. V. Alberghia, G. L. Albert, J. Albicocco, P. Verzini, M. J. Alconada Aleksa, M. Aleksandrov, I. N. Alexab, C. Alexander, G. Alexopoulos, T. Alhroob, M. Ali, B. Aliev, M. Alimontia, G. Alison, J. Alkire, S. P. Allbrooke, B. M. M. Allen, B. W. Allport, P. P. Aloisioa, A. Alonso, A. Alonso, F. Alpigiani, C. Alshehri, A. A. Alstaty, M. Gonzalez, B. Alvarez Piqueras, D. Alvarez Alviggia, M. G. Amadio, B. T. Coutinhoa, Y. Amaral Amelung, C. Amidei, D. Dos Santosa, S. P. Amor Amorima, A. Amoroso, S. Amundsen, G. Anastopoulos, C. Ancu, L. S. Andari, N. Andeen, T. Andersb, C. F. Anders, J. K. Anderson, K. J. Andreazza, A. Andreia, V. Angelidakis, S. Angelozzi, I. Angerami, A. Anisenkovc, A. V. Anjos, N. Annovia, A. Antela, C. Antonelli, M. Antonov, A. Antrim, D. J. Anullia, F. Aoki, M. Bella, L. Aperio Arabidze, G. Arai, Y. Araquea, J. P. Ferraza, V. Araujo Arce, A. T. H. Ardell, R. E. Arduh, F. A. Arguin, J. -F. Argyropoulos, S. Arika, M. Armbruster, A. J. Armitage, L. J. Arnaez, O. Arnold, H. Arratia, M. Arslan, O. Artamonov, A. Artoni, G. Artz, S. Asai, S. Asbah, N. Ashkenazi, A. Asquith, L. Assamagan, K. Astalosa, R. Atkinson, M. Atlay, N. B. Augsten, K. Avolio, G. Axen, B. Ayoub, M. K. Azuelosd, G. Baasa, A. E. Baca, M. J. Bachacou, H. Bachasa, K. Backes, M. Backhaus, M. Bagnaiaa, P. Bahrasemani, H. Baines, J. T. Bajic, M. Baker, O. K. Baldinc, E. M. Balek, P. Balli, F. Balunas, W. K. Banas, E. Banerjeee, Sw. Bannoura, A. A. E. Barak, L. Barberio, E. L. Barberisa, D. Barbero, M. Barillari, T. Barisits, M. -S. Barklow, T. Barlow, N. Barnesc, S. L. Barnett, B. M. Barnett, R. M. Barnovska-Blenessya, Z. Baroncellia, A. Barone, Faculté des Sciences Université Mohamed Premier and LPTPM Oujda Morocco CPPM Aix-Marseille Université and CNRS/IN2P3 Marseille France Homer L. Dodge Department of Physics and Astronomy University of Oklahoma Norman OK USA Department of Physics The University of Texas at Arlington Arlington TX USA Institute of Physics Azerbaijan Academy of Sciences Baku Azerbaijan LAL Univ. Paris-Sud CNRS/IN2P3 Université Paris-Saclay Orsay France Department of Physics University of Toronto Toronto ON Canada Santa Cruz Institute for Particle Physics University of California Santa Cruz Santa Cruz CA USA Department of Physics and Astronomy University of Sussex Brighton UK 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 Center for High Energy Physics University of Oregon Eugene OR USA Department of Physics Stockholm University Stockholm Sweden The Oskar Klein Centre Stockholm Sweden INFN Gruppo Collegato di Udine Sezione di Trieste Udine Italy ICTP Trieste Italy International Center for Elementary Particle Physics and Department of Physics The University of Tokyo Tokyo Japan Faculty of Physics and Applied Computer Science AGH University of Science and Technology Krakow Poland Department of Physics Northern Illinois University DeKalb IL USA Fakultät für Physik Ludwig-Maximilians-Universität München München Germany Particle Physics Department Rutherford Appleton Laboratory Didcot UK Institute of Physics University of Belgrade Belgrade Serbia Department of Physics Alexandru Ioan Cuza University of Iasi Iasi Romania Laboratório de Instrumentação e Física Experimental de Partículas-LIP Lisbon Portugal Departamento de Fisica Teorica y del Cosmos and CAFPE Universidad de Granada Granada Spain Department of Physics Boston University Boston MA USA Institut für Kern- und Teilchenphysik Technische Universität Dresden Dresden Germany INFN

With the increase in energy of the Large Hadron Collider to a centre-of-mass energy of 13 TeV for Run 2, events with dense environments, such as in the cores of highenergy jets, became a focus for new physics searches as well as measurements of the Standard Model. These environments are characterized by charged-particle separations of the order of the tracking detectors sensor granularity. Basic track quantities are compared between 3.2 fb(-1) of data collected by the ATLAS experiment and simulation of protonproton collisions producing high-transverse-momentum jets at a centre-of-mass energy of 13 TeV. The impact of chargedparticle separations and multiplicities on the track reconstruction performance is discussed. The track reconstruction efficiency in the cores of jets with transverse momenta between 200 and 1600 GeV is quantified using a novel, datadriven, method. The method uses the energy loss, dE/ dx, to identify pixel clusters originating from two charged particles. Of the charged particles creating these clusters, themeasured fraction that fail to be reconstructed is 0.061 +/- 0.006 (stat.) +/- 0.014 (syst.) and 0.093 +/- 0.017 (stat.) +/- 0.021 (syst.) for jet transverse momenta of 200-400GeV and 1400-1600GeV, respectively.

关键词： Charged particles

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：