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Inclusive Search for a Highly Boosted Higgs Boson Decaying to a Bottom Quark-Antiquark Pair

Physical Review Letters 2018年第7期120卷 071802-071802页

作者： A. M. Sirunyan A. Tumasyan W. Adam F. Ambrogi E. Asilar T. Bergauer J. Brandstetter E. Brondolin M. Dragicevic J. Erö M. Flechl M. Friedl R. Frühwirth V. M. Ghete J. Grossmann J. Hrubec M. Jeitler A. König N. Krammer I. Krätschmer D. Liko T. Madlener I. Mikulec E. Pree N. Rad H. Rohringer J. Schieck R. Schöfbeck M. Spanring D. Spitzbart W. Waltenberger J. Wittmann C.-E. Wulz M. Zarucki V. Chekhovsky Y. Dydyshka J. Suarez Gonzalez E. A. De Wolf D. Di Croce X. Janssen J. Lauwers M. Van De Klundert H. Van Haevermaet P. Van Mechelen N. Van Remortel S. Abu Zeid F. Blekman J. D’Hondt I. De Bruyn J. De Clercq K. Deroover G. Flouris D. Lontkovskyi S. Lowette S. Moortgat L. Moreels Q. Python K. Skovpen S. Tavernier W. Van Doninck P. Van Mulders I. Van Parijs D. Beghin H. Brun B. Clerbaux G. De Lentdecker H. Delannoy B. Dorney G. Fasanella L. Favart R. Goldouzian A. Grebenyuk G. Karapostoli T. Lenzi J. Luetic T. Maerschalk A. Marinov A. Randle-conde T. Seva E. Starling C. Vander Velde P. Vanlaer D. Vannerom R. Yonamine F. Zenoni F. Zhang A. Cimmino T. Cornelis D. Dobur A. Fagot M. Gul I. Khvastunov D. Poyraz C. Roskas S. Salva M. Tytgat W. Verbeke N. Zaganidis H. Bakhshiansohi O. Bondu S. Brochet G. Bruno C. Caputo A. Caudron P. David S. De Visscher C. Delaere M. Delcourt B. Francois A. Giammanco M. Komm G. Krintiras V. Lemaitre A. Magitteri A. Mertens M. Musich K. Piotrzkowski L. Quertenmont A. Saggio M. Vidal Marono S. Wertz J. Zobec N. Beliy W. L. Aldá Júnior F. L. Alves G. A. Alves L. Brito M. Correa Martins Junior C. Hensel A. Moraes M. E. Pol P. Rebello Teles E. Belchior Batista Das Chagas W. Carvalho J. Chinellato E. Coelho E. M. Da Costa G. G. Da Silveira D. De Jesus Damiao S. Fonseca De Souza L. M. Huertas Guativa H. Malbouisson M. Melo De Almeida C. Mora Herrera L. Mundim H. Nogima L. J. Sanchez Rosas A. Santoro A. Sznajder M. Thiel E. J. Tonelli Manganote F. Torres Da Silva De Araujo A. Vilela Pereira S. Ahuja C. A. Bernardes T. R. Fernandez Perez Tomei E. M. Gregores P. G. Mercadante S. F. Novaes Sandra S. Padu Yerevan Physics Institute Yerevan Armenia Institut für Hochenergiephysik Wien Austria Institute for Nuclear Problems Minsk Belarus Universiteit Antwerpen Antwerpen Belgium Vrije Universiteit Brussel Brussel Belgium Université Libre de Bruxelles Bruxelles Belgium Ghent University Ghent Belgium Université Catholique de Louvain Louvain-la-Neuve Belgium Université de Mons Mons Belgium Centro Brasileiro de Pesquisas Fisicas Rio de Janeiro Brazil Universidade do Estado do Rio de Janeiro Rio de Janeiro Brazil Universidade Estadual Paulista São Paulo Brazil Universidade Federal do ABC São Paulo Brazil Institute for Nuclear Research and Nuclear Energy of Bulgaria Academy of Sciences University of Sofia Sofia Bulgaria Beihang University Beijing China National Centre for Physics Quaid-I-Azam University Islamabad Pakistan Institute of High Energy Physics Beijing China CERN European Organization for Nuclear Research Geneva Switzerland Texas Tech University Lubbock USA State Key Laboratory of Nuclear Physics and Technology Peking University Beijing China Universidad de Los Andes Bogota Colombia University of Split Faculty of Electrical Engineering Mechanical Engineering and Naval Architecture Split Croatia University of Split Faculty of Science Split Croatia Institute Rudjer Boskovic Zagreb Croatia University of Cyprus Nicosia Cyprus Charles University Prague Czech Republic Universidad San Francisco de Quito Quito Ecuador Academy of Scientific Research and Technology of the Arab Republic of Egypt Egyptian Network of High Energy Physics Cairo Egypt National Institute of Chemical Physics and Biophysics Tallinn Estonia Department of Physics University of Helsinki Helsinki Finland Helsinki Institute of Physics Helsinki Finland Lappeenranta University of Technology Lappeenranta Finland IRFU CEA Université Paris-Saclay Gif-sur-Yvette France Saha Institute of Nuclear Physics HBNI Kolkata India Laboratoire Leprince-Ringuet Ecole polytechnique CNRS/IN2P3

An inclusive search for the standard model Higgs boson (H) produced with large transverse momentum (pT) and decaying to a bottom quark-antiquark pair (bb¯) is performed using a data set of pp collisions at s=13 TeV collected with the CMS experiment at the LHC. The data sample corresponds to an integrated luminosity of 35.9 fb−1. A highly Lorentz-boosted Higgs boson decaying to bb¯ is reconstructed as a single, large radius jet, and it is identified using jet substructure and dedicated b tagging techniques. The method is validated with Z→bb¯ decays. The Z→bb¯ process is observed for the first time in the single-jet topology with a local significance of 5.1 standard deviations (5.8 expected). For a Higgs boson mass of 125 GeV, an excess of events above the expected background is observed (expected) with a local significance of 1.5 (0.7) standard deviations. The measured cross section times branching fraction for production via gluon fusion of H→bb¯ with reconstructed pT>450 GeV and in the pseudorapidity range −2.5<η<2.5 is 74±48(stat)−10+17(syst) fb, which is consistent within uncertainties with the standard model prediction.

关键词： Branching fraction W & Z bosons

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Suppression of Excited ϒ States Relative to the Ground State in Pb-Pb Collisions at sNN=5.02 TeV

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Physical Review Letters 2018年第14期120卷 142301-142301页

作者： A. M. Sirunyan A. Tumasyan W. Adam E. Asilar T. Bergauer J. Brandstetter E. Brondolin M. Dragicevic J. Erö M. Flechl M. Friedl R. Frühwirth V. M. Ghete C. Hartl N. Hörmann J. Hrubec M. Jeitler A. König I. Krätschmer D. Liko T. Matsushita I. Mikulec D. Rabady N. Rad B. Rahbaran H. Rohringer J. Schieck J. Strauss W. Waltenberger C.-E. Wulz O. Dvornikov V. Makarenko V. Mossolov J. Suarez Gonzalez V. Zykunov N. Shumeiko S. Alderweireldt E. A. De Wolf X. Janssen J. Lauwers M. Van De Klundert H. Van Haevermaet P. Van Mechelen N. Van Remortel A. Van Spilbeeck S. Abu Zeid F. Blekman J. D’Hondt N. Daci I. De Bruyn K. Deroover S. Lowette S. Moortgat L. Moreels A. Olbrechts Q. Python K. Skovpen S. Tavernier W. Van Doninck P. Van Mulders I. Van Parijs H. Brun B. Clerbaux G. De Lentdecker H. Delannoy G. Fasanella L. Favart R. Goldouzian A. Grebenyuk G. Karapostoli T. Lenzi A. Léonard J. Luetic T. Maerschalk A. Marinov A. Randle-conde T. Seva C. Vander Velde P. Vanlaer D. Vannerom R. Yonamine F. Zenoni F. Zhang T. Cornelis D. Dobur A. Fagot M. Gul I. Khvastunov D. Poyraz S. Salva R. Schöfbeck M. Tytgat W. Van Driessche N. Zaganidis H. Bakhshiansohi O. Bondu S. Brochet G. Bruno A. Caudron S. De Visscher C. Delaere M. Delcourt B. Francois A. Giammanco A. Jafari M. Komm G. Krintiras V. Lemaitre A. Magitteri A. Mertens M. Musich K. Piotrzkowski L. Quertenmont M. Vidal Marono S. Wertz N. Beliy W. L. Aldá Júnior F. L. Alves G. A. Alves L. Brito C. Hensel A. Moraes M. E. Pol P. Rebello Teles E. Belchior Batista Das Chagas W. Carvalho J. Chinellato A. Custódio E. M. Da Costa G. G. Da Silveira D. De Jesus Damiao C. De Oliveira Martins S. Fonseca De Souza L. M. Huertas Guativa H. Malbouisson D. Matos Figueiredo C. Mora Herrera L. Mundim H. Nogima W. L. Prado Da Silva A. Santoro A. Sznajder E. J. Tonelli Manganote F. Torres Da Silva De Araujo A. Vilela Pereira S. Ahuja C. A. Bernardes S. Dogra T. R. Fernandez Perez Tomei E. M. Gregores P. G. Mercadante C. S. Moon S. F. Novaes Sandra S. Padula D. Romero Abad J. C. Ruiz Vargas A. Aleksandr Yerevan Physics Institute Yerevan Armenia Institut für Hochenergiephysik Wien Austria Institute for Nuclear Problems Minsk Belarus National Centre for Particle and High Energy Physics Minsk Belarus Universiteit Antwerpen Antwerpen Belgium Vrije Universiteit Brussel Brussel Belgium Université Libre de Bruxelles Bruxelles Belgium Ghent University Ghent Belgium Université Catholique de Louvain Louvain-la-Neuve Belgium Université de Mons Mons Belgium Centro Brasileiro de Pesquisas Fisicas Rio de Janeiro Brazil Universidade do Estado do Rio de Janeiro Rio de Janeiro Brazil Universidade Estadual Paulista São Paulo Brazil Universidade Federal do ABC São Paulo Brazil Institute for Nuclear Research and Nuclear Energy Sofia Bulgaria University of Sofia Sofia Bulgaria Beihang University Beijing China National Centre for Physics Quaid-I-Azam University Islamabad Pakistan Institute of High Energy Physics Beijing China CERN European Organization for Nuclear Research Geneva Switzerland Texas Tech University Lubbock USA State Key Laboratory of Nuclear Physics and Technology Peking University Beijing China Universidad de Los Andes Bogota Colombia University of Split Faculty of Electrical Engineering Mechanical Engineering and Naval Architecture Split Croatia University of Split Faculty of Science Split Croatia Institute Rudjer Boskovic Zagreb Croatia University of Cyprus Nicosia Cyprus Charles University Prague Czech Republic Universidad San Francisco de Quito Quito Ecuador Academy of Scientific Research and Technology of the Arab Republic of Egypt Egyptian Network of High Energy Physics Cairo Egypt National Institute of Chemical Physics and Biophysics Tallinn Estonia Department of Physics University of Helsinki Helsinki Finland Helsinki Institute of Physics Helsinki Finland Lappeenranta University of Technology Lappeenranta Finland IRFU CEA Université Paris-Saclay Gif-sur-Yvette France Saha Institute of Nuclear Physics HBNI KolkataIndia Laboratoir

The relative yields of ϒ mesons produced in pp and Pb-Pb collisions at sNN=5.02 TeV and reconstructed via the dimuon decay channel are measured using data collected by the CMS experiment. Double ratios are formed by comparing the yields of the excited states, ϒ(2S) and ϒ(3S), to the ground state, ϒ(1S), in both Pb-Pb and pp collisions at the same center-of-mass energy. The double ratios, [ϒ(nS)/ϒ(1S)]Pb−Pb/[ϒ(nS)/ϒ(1S)]pp, are measured to be 0.308±0.055(stat)±0.019(syst) for the ϒ(2S) and less than 0.26 at 95% confidence level for the ϒ(3S). No significant ϒ(3S) signal is found in the Pb-Pb data. The double ratios are studied as a function of collision centrality, as well as ϒ transverse momentum and rapidity. No significant dependencies are observed.

关键词： Jets & heavy flavor physics QCD in nuclear reactions Quark-gluon plasma Bottom mesons

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Improved protein residue-residue contacts prediction using learning-to-rank

Improved protein residue-residue contacts prediction using l...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Xiaoyang Jing Qiwen Dong School of Computer Science Fudan University Shanghai People's Republic of China Shanghai Key Laboratory of Intelligent Information Processing Shanghai People's Republic of China Key Laboratory of Network Oriented Intelligent Computation Harbin Institute of Technology Shenzhen Graduate School Shenzhen Guangdong People's Republic of China Institute for Data Science and Engineering East China Normal University Shanghai People's Republic of China

ISBN: (纸本)9781509016129

Protein residue-residue contacts dictate the topology of protein structure and play an important role in structural biology, especially in de novo protein structure prediction. Accurate prediction of residue contacts could improve the performance of de novo protein structure prediction methods. In this study, a novel method based on learning-to-rank (RRCRank) has been presented to predict protein residue-residue contacts. The proposed method formulates the contacts prediction problem as a ranking problem. Firstly, the contact probabilities of residue pairs are predicted by ensemble machine-learning classifiers and correlated mutations approaches. And then, the proposed method integrates the complementary outputs of machine-learning and correlated mutations approaches and uses the learning-to-rank algorithm to rank residue pairs based on their probabilities to be contacts. Benchmarked on the CASP11 dataset, the proposed method achieves an improved performance for all three categories of contacts (short-range, medium-range and long-range contacts), which shows the proposed method based on learning-to-rank could take advantage of machine-learning and correlated mutations approaches and could provide the state-of-the-art performance.

关键词： Proteins Protein engineering Training Predictive models Feature extraction Classification algorithms Prediction algorithms

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Adaptive piecewise elastic motion estimation 11th

Adaptive piecewise elastic motion estimation

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11th International Conference on Intelligent computing, ICIC 2015

作者： Di, Huijun Tao, Linmi Xu, Guangyou Beijing Key Laboratory of Intelligent Information Technology School of Computer Science Beijing Institute of Technology Beijing100081 China Key Laboratory of Pervasive Computing Ministry of Education Department of Computer Science and Technology Tsinghua University Beijing100084 China

ISBN: (纸本)9783319221854

This paper proposes a novel probabilistic graphical model, called MTHMM-P, for partitioning general nonrigid motion into piecewise elastic motion, so as to achieve nonrigid motion estimation without the need of any a priori shape model. To this end, two interrelated sub-problems have to be addressed: partitioning whole motion sequence into several coherent pieces and estimating elastic motion inside each one. The proposed MTHMM-P jointly formulates these two sub-problems. By means of a competition-cooperation partition mechanism and joint inference algorithm, the MTHMM-P can automatically determine the number of pieces as well as adjust the span of each piece by adapting to the input sequence, and at the same time achieve the estimation of piecewise elastic motion. Experiments on the motion of face and body show the capability of the MTHMM-P. © Springer International Publishing Switzerland 2015.

关键词： Motion estimation

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Constructing Edge-Colored Graph for Heterogeneous networks

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Journal of Computer science & technology 2015年第5期30卷 1154-1160页

作者：侯睿武继刚陈亚文张海波隋秀峰 School of Computer Science and Software Engineering Tianjin Polytechnic University Tianjin 300387 China State Key Laboratory of Computer Architecture~ Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Department of Computer Science University of Otago Dunedin 9054 New Zealand

In order to build a fault-tolerant network, heterogeneous facilities are arranged in the network to prevent homogeneous faults from causing serious damage. This paper uses edge-colored graph to investigate the features of a network topology which is survivable after a set of homogeneous devices malfunction. We propose an approach to designing such networks under arbitrary parameters. We also show that the proposed approach can be used to optimize inter-router connections in network-on-chip to reduce the additional consum!otion of energy and time delay.

关键词： network reliability homogeneous fault fault tolerance reconfigurable system network-on-chip

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Hug the Elephant: Migrating a Legacy data Analytics Application to Hadoop Ecosystem

Hug the Elephant: Migrating a Legacy Data Analytics Applicat...

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International Conference on Software Maintenance (ICSM)

作者： Feng Zhu Jie Liu Sa Wang Jiwei Xu Lijie Xu Jixin Ren Dan Ye Jun Wei Tao Huang University of Chinese Academy of Sciences State Key Laboratory of Computer Science Chinese Academy of Sciences Institute of Computing Chinese Academy of Sciences Institute of Software Chinese Academy of Sciences Xin Yi Hua Medical Technology Company Zhengzhou Henan

ISBN: (纸本)9781509038077

Big data applications that rely on relational databases gradually expose limitations on scalability and performance. In recent years, Hadoop ecosystem has been widely adopted as an evolving solution. This paper presents the migration of a legacy data analytics application in a provincial data center. The target platform follows "no one size fits all" method. Considering different workloads, data storage is hybrid with distributed file system (HDFS) and distributed NoSQL database. Beyond the architecture re-design, we focus on the problem of data model transformation from relational database to NoSQL database. We propose a query-aware approach to free developers from tedious manual work. The approach generates query-specific views (NoView) for NoSQL and re-structures the views to align with NoSQL's data model. Our results show that the migrated application achieves high scalability and high performance. We believe that our practice provides valuable insights (such as NoSQL data modeling methodology), and the techniques can be easily applied to other similar migrations.

关键词： data models Ecosystems Relational databases Big data data analysis Distributed databases Computer architecture

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A decade of Gamma-Ray Bursts observed by Fermi-LAT:

arXiv

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arXiv 2019年

作者： Ajello, M. Arimoto, M. Axelsson, M. Baldini, L. Barbiellini, G. Bastieri, D. Bellazzini, R. Bhat, P.N. Bissaldi, E. Blandford, R.D. Bonino, R. Bonnell, J. Bottacini, E. Bregeon, J. Bruel, P. Buehler, R. Cameron, R.A. Caputo, R. Caraveo, P.A. Cavazzuti, E. Chen, S. Cheung, C.C. Chiaro, G. Ciprini, S. Costantin, D. Crnogorcevic, M. Cutini, S. Dainotti, M. D’Ammando, F. de la Torre Luque, P. de Palma, F. Desai, A. Desiante, R. Di Lalla, N. Di Venere, L. Fana Dirirsa, F. Fegan, S.J. Franckowiak, A. Fukazawa, Y. Funk, S. Fusco, P. Gargano, F. Gasparrini, D. Giglietto, N. Giordano, F. Giroletti, M. Green, D. Grenier, I.A. Grove, J.E. Guiriec, S. Hays, E. Hewitt, J.W. Horan, D. Jóhannesson, G. Kocevski, D. Kuss, M. Latronico, L. Li, J. Longo, F. Loparco, F. Lovellette, M.N. Lubrano, P. Maldera, S. Manfreda, A. Martí-Devesa, G. Mazziotta, M.N. Mereu, I. Meyer, M. Michelson, P.F. Mirabal, N. Mitthumsiri, W. Mizuno, T. Monzani, M.E. Moretti, E. Morselli, A. Moskalenko, I.V. Negro, M. Nuss, E. Ohno, M. Omodei, N. Orienti, M. Orlando, E. Palatiello, M. Paliya, V.S. Paneque, D. Persic, M. Pesce-Rollins, M. Petrosian, V. Piron, F. Poolakkil, S. Poon, H. Porter, T.A. Principe, G. Racusin, J.L. Rainò, S. Rando, R. Razzano, M. Razzaque, S. Reimer, A. Reimer, O. Reposeur, T. Ryde, F. Serini, D. Sgrò, C. Siskind, E.J. Sonbas, E. Spandre, G. Spinelli, P. Suson, D.J. Tajima, H. Takahashi, M. Tak, D. Thayer, J.B. Torres, D.F. Troja, E. Valverde, J. Veres, P. Vianello, G. von Kienlin, A. Wood, K. Yassine, M. Zhu, S. Zimmer, S. Department of Physics and Astronomy Clemson University Kinard Lab of Physics ClemsonSC29634-0978 United States Faculty of Mathematics and Physics Institute of Science and Engineering Kanazawa University Kakuma Kanazawa Ishikawa920-1192 Department of Physics and Oskar Klein Center for Cosmoparticle Physics Stockholm University Stockholm106 91 Sweden Department of Physics KTH Royal Institute of Technology AlbaNova StockholmSE-106 91 Sweden Università di Pisa Istituto Nazionale di Fisica Nucleare Sezione di Pisa PisaI-56127 Italy Istituto Nazionale di Fisica Nucleare Sezione di Trieste TriesteI-34127 Italy Dipartimento di Fisica Università di Trieste TriesteI-34127 Italy Istituto Nazionale di Fisica Nucleare Sezione di Padova PadovaI-35131 Italy Dipartimento di Fisica e Astronomia "G. Galilei" Università di Padova PadovaI-35131 Italy Istituto Nazionale di Fisica Nucleare Sezione di Pisa PisaI-56127 Italy University of Alabama in Huntsville HuntsvilleAL35899 United States Dipartimento di Fisica "M. Merlin" dell’Università e del Politecnico di Bari BariI-70126 Italy Istituto Nazionale di Fisica Nucleare Sezione di Bari BariI-70126 Italy W. W. Hansen Experimental Physics Laboratory Kavli Institute for Particle Astrophysics and Cosmology Department of Physics SLAC National Accelerator Laboratory Stanford University StanfordCA94305 United States Istituto Nazionale di Fisica Nucleare Sezione di Torino TorinoI-10125 Italy Dipartimento di Fisica Università degli Studi di Torino TorinoI-10125 Italy NASA Goddard Space Flight Center GreenbeltMD20771 United States Department of Astronomy University of Maryland College ParkMD20742 United States Department of Physics and Astronomy University of Padova Vicolo Osservatorio 3 PadovaI-35122 Italy Laboratoire Univers et Particules de Montpellier Université Montpellier CNRS/IN2P3 MontpellierF-34095 France Laboratoire Leprince-Ringuet École polytechnique CNRS/IN2P3 PalaiseauF-91128 France

The Large Area Telescope (LAT) aboard the Fermi spacecraft routinely observes high-energy emission from gamma-ray bursts (GRBs). Here we present the second catalog of LAT-detected GRBs, covering the first 10 years of operations, from 2008 August 4 to 2018 August 4. A total of 186 GRBs are found;of these, 91 show emission in the range 30–100 MeV (17 of which are seen only in this band) and 169 are detected above 100 MeV. Most of these sources were discovered by other instruments (Fermi/GBM, Swift/BAT, AGILE, INTEGRAL) or reported by the Interplanetary network (IPN);the LAT has independently triggered on 4 GRBs. This catalog presents the results for all 186 GRBs. We study onset, duration and temporal properties of each GRB, as well as spectral characteristics in the 100 MeV–100 GeV energy range. Particular attention is given to the photons with highest energy. Compared with the first LAT GRB catalog, our rate of detection is significantly improved. The results generally confirm the main findings of the first catalog: the LAT primarily detects the brightest GBM bursts, and the high-energy emission shows delayed onset as well as longer duration. However, in this work we find delays exceeding 1 ks, and several GRBs with durations over 10 ks. Furthermore, the larger number of LAT detections shows that these GRBs cover not only the high-fluence range of GBM-detected GRBs, but also samples lower fluences. In addition, the greater number of detected GRBs with redshift estimates allows us to study their properties in both the observer and rest frames. Comparison of the observational results with theoretical predictions reveals that no model is currently able to explain all results, highlighting the role of LAT observations in driving theoretical models. Copyright © 2019, The Authors. All rights reserved.

关键词： Stars

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Using recurrent neural networks toward black-box system anomaly prediction

Using recurrent neural networks toward black-box system anom...

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International Workshop on Quality of Service

作者： Shaohan Huang Carol Fung Kui Wang Polo Pei Zhongzhi Luan Depei Qian Sino-German Joint Software Institute Beihang University Beijing China Computer Science Department Virginia Commonwealth University Richmond Virginia USA Beijing municipal key laboratory of network technology Beihang University Beijing China

Component based enterprise systems are becoming extremely complex in which the availability and usability are influenced intensively by the system's anomalies. Anomaly prediction is highly important for ensuring a system's stability, which aims at preventing anomaly from occurring through pre-failure warning. However, due to the system's complex nature and the noise from monitoring, capturing pre-failure symptoms is a challenging problem. In this paper, we present a sequential and an averaged recurrent neural networks (RNN) models for distributed systems and component based systems. Specifically, we use cycle representation to capture cyclical system behaviors, which can be used to improve prediction accuracy. The anomaly data used in the experiments is collected from RUBis, IBM System S, and the component based system of enterprise T. The experimental results show that our proposed methods can achieve high prediction accuracy with satisfying lead time. Our recurrent neural networks model also demonstrates time efficiency for monitoring large-scale systems.

关键词： Monitoring Predictive models Recurrent neural networks Measurement Markov processes Time series analysis

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Search for Pair-Produced Resonances Each Decaying into at Least Four Quarks in Proton-Proton Collisions at s=13 TeV

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Physical Review Letters 2018年第14期121卷 141802-141802页

作者： A. M. Sirunyan A. Tumasyan W. Adam F. Ambrogi E. Asilar T. Bergauer J. Brandstetter M. Dragicevic J. Erö A. Escalante Del Valle M. Flechl R. Frühwirth V. M. Ghete J. Hrubec M. Jeitler N. Krammer I. Krätschmer D. Liko T. Madlener I. Mikulec N. Rad H. Rohringer J. Schieck R. Schöfbeck M. Spanring D. Spitzbart A. Taurok W. Waltenberger J. Wittmann C.-E. Wulz M. Zarucki V. Chekhovsky V. Mossolov J. Suarez Gonzalez E. A. De Wolf D. Di Croce X. Janssen J. Lauwers M. Pieters M. Van De Klundert H. Van Haevermaet P. Van Mechelen N. Van Remortel S. Abu Zeid F. Blekman J. D’Hondt I. De Bruyn J. De Clercq K. Deroover G. Flouris D. Lontkovskyi S. Lowette I. Marchesini S. Moortgat L. Moreels Q. Python K. Skovpen S. Tavernier W. Van Doninck P. Van Mulders I. Van Parijs D. Beghin B. Bilin H. Brun B. Clerbaux G. De Lentdecker H. Delannoy B. Dorney G. Fasanella L. Favart R. Goldouzian A. Grebenyuk A. K. Kalsi T. Lenzi J. Luetic N. Postiau E. Starling L. Thomas C. Vander Velde P. Vanlaer D. Vannerom Q. Wang T. Cornelis D. Dobur A. Fagot M. Gul I. Khvastunov D. Poyraz C. Roskas D. Trocino M. Tytgat W. Verbeke B. Vermassen M. Vit N. Zaganidis H. Bakhshiansohi O. Bondu S. Brochet G. Bruno C. Caputo P. David C. Delaere M. Delcourt B. Francois A. Giammanco G. Krintiras V. Lemaitre A. Magitteri A. Mertens M. Musich K. Piotrzkowski A. Saggio M. Vidal Marono S. Wertz J. Zobec F. L. Alves G. A. Alves L. Brito M. Correa Martins Junior G. Correia Silva C. Hensel A. Moraes M. E. Pol P. Rebello Teles E. Belchior Batista Das Chagas W. Carvalho J. Chinellato E. Coelho E. M. Da Costa G. G. Da Silveira D. De Jesus Damiao C. De Oliveira Martins S. Fonseca De Souza H. Malbouisson D. Matos Figueiredo M. Melo De Almeida C. Mora Herrera L. Mundim H. Nogima W. L. Prado Da Silva L. J. Sanchez Rosas A. Santoro A. Sznajder M. Thiel E. J. Tonelli Manganote F. Torres Da Silva De Araujo A. Vilela Pereira S. Ahuja C. A. Bernardes L. Calligaris T. R. Fernandez Perez Tomei E. M. Gregores P. G. Mercadante S. F. Novaes Sandra S. Padula D. Romero Abad A. Aleksandrov Yerevan Physics Institute Yerevan Armenia Institut für Hochenergiephysik Wien Austria Institute for Nuclear Problems Minsk Belarus Universiteit Antwerpen Antwerpen Belgium Vrije Universiteit Brussel Brussel Belgium Université Libre de Bruxelles Bruxelles Belgium The University of Kansas Lawrence Kansas USA Ghent University Ghent Belgium Université Catholique de Louvain Louvain-la-Neuve Belgium Centro Brasileiro de Pesquisas Fisicas Rio de Janeiro Brazil Universidade do Estado do Rio de Janeiro Rio de Janeiro Brazil Universidade Estadual Paulista São Paulo Brazil Universidade Federal do ABC São Paulo Brazil Institute for Nuclear Research and Nuclear Energy Bulgarian Academy of Sciences Sofia Bulgaria University of Sofia Sofia Bulgaria Beihang University Beijing China National Centre for Physics Quaid-I-Azam University Islamabad Pakistan Institute of High Energy Physics Beijing China CERN European Organization for Nuclear Research Geneva Switzerland Texas Tech University Lubbock Texas USA State Key Laboratory of Nuclear Physics and Technology Peking University Beijing China University of Virginia Charlottesville Virginia USA Universidad de Los Andes Bogota Colombia University of Split Faculty of Electrical Engineering Mechanical Engineering and Naval Architecture Split Croatia University of Split Faculty of Science Split Croatia Institute Rudjer Boskovic Zagreb Croatia University of Cyprus Nicosia Cyprus Charles University Prague Czech Republic Escuela Politecnica Nacional Quito Ecuador Universidad San Francisco de Quito Quito Ecuador Academy of Scientific Research and Technology of the Arab Republic of Egypt Egyptian Network of High Energy Physics Cairo Egypt National Institute of Chemical Physics and Biophysics Tallinn Estonia Department of Physics University of Helsinki Helsinki Finland Helsinki Institute of Physics Helsinki Finland Lappeenranta University of Technology Lappeenranta Finland IRFU CEA Université Paris-Saclay Gif-s

This Letter presents the results of a search for pair-produced particles of masses above 100 GeV that each decay into at least four quarks. Using data collected by the CMS experiment at the LHC in 2015–2016, corresponding to an integrated luminosity of 38.2 fb−1, reconstructed particles are clustered into two large jets of similar mass, each consistent with four-parton substructure. No statistically significant excess of data over the background prediction is observed in the distribution of average jet mass. Pair-produced squarks with dominant hadronic R-parity-violating decays into four quarks and with masses between 0.10 and 0.72 TeV are excluded at 95% confidence level. Similarly, pair-produced gluinos that decay into five quarks are also excluded with masses between 0.10 and 1.41 TeV at 95% confidence level. These are the first constraints that have been placed on pair-produced particles with masses below 400 GeV that decay into four or five quarks, bridging a significant gap in the coverage of R-parity-violating supersymmetry parameter space.

关键词： Particle production Supersymmetric models Quarks Superpartners Hadron colliders

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Flickr group recommendation via heterogeneous information networks 15

Flickr group recommendation via heterogeneous information ne...

引用

7th International Conference on Internet Multimedia computing and Service, ICIMCS 2015

作者： Wang, Yueyang Xia, Yuanfang Tang, Siliang Wu, Fei Zhuang, Yueting College of Computer Science and Technology Zhejiang University Key Laboratory of Big Data Intelligent Computing of Zhejiang Province Innovation Joint Research Center for ICPS China

ISBN: (纸本)9781450335287

As an important characteristic of social media (i.e. Flickr or Facebook), user communities or groups are beginning to attract increasing attention. Most of the previous studies on group recommendation only consider a homogeneous relationship, such as the rating of users to groups in social network. In real world, each group has its textual descriptions (e.g. the "Sky & Cloud" group in Flickr), and the describing words about a given group may mention particular entities as well as their belonging categories (e.g. "Nature"). In fact, the group recommendation can be conducted in a heterogeneous information network, where informative cues are in general multi-typed. Motivated by the assumption that different types of relationships in heterogeneous information network can be potentially used to boost the performance of the group recommendation. We propose to combine heterogeneous relationship information for users with implicit user feedback. In general, the group recommendation in this paper is formulated as a non-negative matrix factorization (NMF) method regularized with user-user similarity via heterogeneous information networks. Experiments show that our proposed approach outperforms other counterpart recommendation techniques. © 2015 ACM.

关键词： Non-negative matrix factorization

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