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arXiv 2017年

作者： Gui, Lin Hu, Jiannan He, Yulan Xu, Ruifeng Lu, Qin Du, Jiachen Shenzhen Graduate School Harbin Institute of Technology College of Mathematics and Computer Science Fuzhou University School of Engineering and Applied Science Aston University Guangdong Provincial Engineering Technology Research Center for Data Science Department of Computing Hong Kong Polytechnic University

Emotion cause extraction aims to identify the reasons behind a certain emotion expressed in text. It is a much more difficult task compared to emotion classification. Inspired by recent advances in using deep memory networks for question answering (QA), we propose a new approach which considers emotion cause identification as a reading comprehension task in QA. Inspired by convolutional neural networks, we propose a new mechanism to store relevant context in different memory slots to model context information. Our proposed approach can extract both word level sequence features and lexical features. Performance evaluation shows that our method achieves the state-of-the-art performance on a recently released emotion cause dataset, outperforming a number of competitive baselines by at least 3.01% in F-measure. Copyright © 2017, The Authors. All rights reserved.

关键词： Extraction

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Quantum computing at the frontiers of biological sciences

arXiv

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arXiv 2019年

作者： Emani, Prashant S. Warrell, Jonathan Anticevic, Alan Bekiranov, Stefan Gandal, Michael McConnell, Michael J. Sapiro, Guillermo Aspuru-Guzik, Alán Baker, Justin Bastiani, Matteo McClure, Patrick Murray, John Sotiropoulos, Stamatios N. Taylor, Jacob Senthil, Geetha Lehner, Thomas Gerstein, Mark B. Harrow, Aram W. Program in Computational Biology and Bioinformatics Yale University New HavenCT06520 United States Department of Molecular Biophysics and Biochemistry Yale University New HavenCT06520 United States Yale School of Medicine Department of Psychiatry New HavenCT06511 United States University of Virginia School of Medicine Department of Biochemistry and Molecular Genetics CharlottesvilleVA22903 United States Department of Psychiatry Semel Institute David Geffen School of Medicine University of California–Los Angeles 695 Charles E. Young Drive South Los AngelesCA90095 United States Univ. of Virginia School of Medicine Department of Neuroscience CharlottesvilleVA22903 United States Department of Electrical and Computer Engineering Duke University DurhamNC27708 United States Department of Chemistry University of Toronto 80 St. George Street TorontoONM5S 3H6 Canada TorontoONM5S 1M1 Canada CIFAR Artificial Intelligence Research Chair Vector Institute TorontoONM5S 1M1 Canada Department of Computer Science University of Toronto 40 St. George Street TorontoONM5S 2E4 Canada Schizophrenia and Bipolar Disorder Program McLean Hospital BelmontMA02478 United States Department of Psychiatry Harvard Medical School BostonMA02114 United States Sir Peter Mansfield Imaging Centre School of Medicine University of Nottingham NottinghamNG7 2RD United Kingdom Machine Learning Team National Institute of Mental Health BethesdaMD20892 United States Section on Functional Imaging Methods National Institute of Mental Health BethesdaMD20892 United States Department of Psychiatry Yale University School of Medicine New HavenCT06511 United States Department of Physics Yale University New HavenCT06511 United States Joint Center for Quantum Information and Computer Science University of Maryland College ParkMD20742 United States National Institute of Standards and Technology GaithersburgMD20899 United States Office of Genomics Research Coordination N

The search for meaningful structure in biological data has relied on cutting-edge advances in computational technology and data science methods. However, challenges arise as we push the limits of scale and complexity in biological problems. Innovation in massively parallel, classical computing hardware and algorithms continues to address many of these challenges, but there is a need to simultaneously consider new paradigms to circumvent current barriers to processing speed. Accordingly, we articulate a view towards quantum computation and quantum information science, where algorithms have demonstrated potential polynomial and exponential computational speedups in certain applications, such as machine learning. The maturation of the field of quantum computing, in hardware and algorithm development, also coincides with the growth of several collaborative efforts to address questions across length and time scales, and scientific disciplines. We use this coincidence to explore the potential for quantum computing to aid in one such endeavor: the merging of insights from genetics, genomics, neuroimaging and behavioral phenotyping. By examining joint opportunities for computational innovation across fields, we highlight the need for a common language between biological data analysis and quantum computing. Ultimately, we consider current and future prospects for the employment of quantum computing algorithms in the biological sciences. Copyright © 2019, The Authors. All rights reserved.

关键词： Machine learning

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Is the winner really the best? A critical analysis of common research practice in biomedical image analysis competitions

arXiv

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arXiv 2018年

作者： Maier-Hein, Lena Eisenmann, Matthias Reinke, Annika Onogur, Sinan Stankovic, Marko Scholz, Patrick Arbel, Tal Bogunovic, Hrvoje Bradley, Andrew P. Carass, Aaron Carolin Feldmann Frangi, Alejandro F. Ful, Peter M. van Ginneken, Bram Hanbury, Allan Honauer, Katrin Kozubek, Michal Landman, Bennett A. Marz, Keno Maier, Oskar Maier-Hein, Klaus Menze, Bjoern H. Müller, Henning Neher, Peter F. Niessen, Wiro Rajpoot, Nasir Sharp, Gregory C. Sirinukunwattana, Korsuk Speidel, Stefanie Stock, Christian Stoyanov, Danail Taha, Abdel Aziz van der Sommen, Fons Wang, Ching-Wei Weber, Marc-André Zheng, Guoyan Jannin, Pierre Kopp-Schneider, Annette Heidelberg Germany Centre for Intelligent Machines McGill University MontrealQC Canada Christian Doppler Laboratory for Ophthalmic Image Analysis Department of Ophthalmology Medical University Vienna Vienna Austria Science and Engineering Faculty Queensland University of Technology BrisbaneQLD Australia Department of Electrical and Computer Engineering Department of Computer Science Johns Hopkins University Baltimore United States CISTIB Centre for Computational Imaging and Simulation Technologies in Biomedicine University of Sheffield Sheffield United Kingdom Department of Radiology and Nuclear Medicine Medical Image Analysis Radboud University Center Nijmegen Netherlands Institute of Information Systems Engineering TU Wien Vienna Austria Heidelberg University Heidelberg Germany Centre for Biomedical Image Analysis Masaryk University Brno Czech Republic Electrical Engineering Vanderbilt University NashvilleTN United States Institute of Medical Informatics Universität zu Lübeck Lübeck Germany Heidelberg Germany Institute for Advanced Studies Department of Informatics Technical University of Munich Munich Germany Information System Institute HES-SO Sierre Switzerland Departments of Radiology Nuclear Medicine and Medical Informatics Erasmus MC Rotterdam Netherlands Department of Computer Science University of Warwick Coventry United Kingdom Department of Radiation Oncology Massachusetts General Hospital BostonMA United States Institute of Biomedical Engineering University of Oxford Oxford United Kingdom National Center for Tumor Diseases Dresden Dresden Germany Heidelberg Germany Department of Computer Science University College London London United Kingdom Data Science Studio Research Studios Austria FG Vienna Austria Department of Electrical Engineering Eindhoven University of Technology Eindhoven Netherlands AIExplore NTUST Center of Computer Vision and Medical Imaging Graduate Institute of Biomedical Engineering National Ta

International challenges have become the standard for validation of biomedical image analysis methods. Given their scientific impact, it is surprising that a critical analysis of common practices related to the organization of challenges has not yet been performed. In this paper, we present a comprehensive analysis of biomedical image analysis challenges conducted up to now. We demonstrate the importance of challenges and show that the lack of quality control has critical consequences. First, reproducibility and interpretation of the results is often hampered as only a fraction of relevant information is typically provided. Second, the rank of an algorithm is generally not robust to a number of variables such as the test data used for validation, the ranking scheme applied and the observers that make the reference annotations. To overcome these problems, we recommend best practice guidelines and define open research questions to be addressed in the future. Copyright © 2018, The Authors. All rights reserved.

关键词： Quality control

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Branching Fraction Measurements of the Rare Bs0→ϕμ+μ− and Bs0→f2′(1525)μ+μ− Decays

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Physical Review Letters 2021年第15期127卷 151801-151801页

作者： R. Aaij C. Abellán Beteta T. Ackernley B. Adeva M. Adinolfi H. Afsharnia C. A. aidala S. aiola Z. Ajaltouni S. Akar J. Albrecht F. Alessio M. Alexander A. Alfonso Albero Z. Aliouche G. Alkhazov P. Alvarez Cartelle S. Amato Y. Amhis L. An L. Anderlini A. Andreianov M. Andreotti F. Archilli A. Artamonov M. Artuso K. Arzymatov E. Aslanides M. Atzeni B. Audurier S. Bachmann M. Bachmayer J. J. Back P. Baladron Rodriguez V. Balagura W. Baldini J. Baptista Leite R. J. Barlow S. Barsuk W. Barter M. Bartolini F. Baryshnikov J. M. Basels G. Bassi B. Batsukh A. Battig A. Bay M. Becker F. Bedeschi I. Bediaga A. Beiter V. Belavin S. Belin V. Bellee K. Belous I. Belov I. Belyaev G. Bencivenni E. Ben-Haim A. Berezhnoy R. Bernet D. Berninghoff H. C. Bernstein C. Bertella A. Bertolin C. Betancourt F. Betti Ia. Bezshyiko S. Bhasin J. Bhom L. Bian M. S. Bieker S. Bifani P. Billoir M. Birch F. C. R. Bishop A. Bitadze A. Bizzeti M. Bjørn M. P. Blago T. Blake F. Blanc S. Blusk D. Bobulska J. A. Boelhauve O. Boente Garcia T. Boettcher A. Boldyrev A. Bondar N. Bondar S. Borghi M. Borisyak M. Borsato J. T. Borsuk S. A. Bouchiba T. J. V. Bowcock A. Boyer C. Bozzi M. J. Bradley S. Braun A. Brea Rodriguez M. Brodski J. Brodzicka A. Brossa Gonzalo D. Brundu A. Buonaura C. Burr A. Bursche A. Butkevich J. S. Butter J. Buytaert W. Byczynski S. Cadeddu H. Cai R. Calabrese L. Calefice L. Calero Diaz S. Cali R. Calladine M. Calvi M. Calvo Gomez P. Camargo Magalhaes P. Campana A. F. Campoverde Quezada S. Capelli L. Capriotti A. Carbone G. Carboni R. Cardinale A. Cardini I. Carli P. Carniti L. Carus K. Carvalho Akiba A. Casais Vidal G. Casse M. Cattaneo G. Cavallero S. Celani J. Cerasoli A. J. Chadwick M. G. Chapman M. Charles Ph. Charpentier G. Chatzikonstantinidis C. A. Chavez Barajas M. Chefdeville C. Chen S. Chen A. Chernov V. Chobanova S. Cholak M. Chrzaszcz A. Chubykin V. Chulikov P. Ciambrone M. F. Cicala X. Cid Vidal G. Ciezarek P. E. L. Clarke M. Clemencic H. V. Cliff J. Closier J. L. Cobbledick V. Coco J. A. B. Coelho J. Cogan E. Cogneras Nikhef National Institute for Subatomic Physics Amsterdam Netherlands Physik-Institut Universität Zürich Zürich Switzerland Oliver Lodge Laboratory University of Liverpool Liverpool United Kingdom Instituto Galego de Física de Altas Enerxías (IGFAE) Universidade de Santiago de Compostela Santiago de Compostela Spain H.H. Wills Physics Laboratory University of Bristol Bristol United Kingdom Université Clermont Auvergne CNRS/IN2P3 LPC Clermont-Ferrand France University of Michigan Ann Arbor USA (associated with Syracuse University Syracuse New York USA) INFN Sezione di Milano Milano Italy University of Cincinnati Cincinnati Ohio USA Fakultät Physik Technische Universität Dortmund Dortmund Germany European Organization for Nuclear Research (CERN) Geneva Switzerland School of Physics and Astronomy University of Glasgow Glasgow United Kingdom ICCUB Universitat de Barcelona Barcelona Spain Department of Physics and Astronomy University of Manchester Manchester United Kingdom Petersburg Nuclear Physics Institute NRC Kurchatov Institute (PNPI NRC KI) Gatchina Russia Cavendish Laboratory University of Cambridge Cambridge United Kingdom Universidade Federal do Rio de Janeiro (UFRJ) Rio de Janeiro Brazil Université Paris-Saclay CNRS/IN2P3 IJCLab Orsay France INFN Sezione di Firenze Firenze Italy INFN Sezione di Ferrara Ferrara Italy Physikalisches Institut Ruprecht-Karls-Universität Heidelberg Heidelberg Germany Institute for High Energy Physics NRC Kurchatov Institute (IHEP NRC KI) Protvino Russia Protvino Russia Syracuse University Syracuse New York USA Yandex School of Data Analysis Moscow Russia Aix Marseille Univ CNRS/IN2P3 CPPM Marseille France Laboratoire Leprince-Ringuet CNRS/IN2P3 Ecole Polytechnique Institut Polytechnique de Paris Palaiseau France Institute of Physics Ecole Polytechnique Fédérale de Lausanne (EPFL) Lausanne Switzerland Department of Physics University of Warwick Coventry United Kingdom Centro Brasileiro de Pesquisa

The branching fraction of the rare Bs0→ϕμ+μ− decay is measured using data collected by the LHCb experiment at center-of-mass energies of 7, 8, and 13 TeV, corresponding to integrated luminosities of 1, 2, and 6 fb−1, respectively. The branching fraction is reported in intervals of q2, the square of the dimuon invariant mass. In the q2 region between 1.1 and 6.0 GeV2/c4, the measurement is found to lie 3.6 standard deviations below a standard model prediction based on a combination of light cone sum rule and lattice QCD calculations. In addition, the first observation of the rare Bs0→f2′(1525)μ+μ− decay is reported with a statistical significance of 9 standard deviations and its branching fraction is determined.

关键词： Branching fraction Flavor changing neutral currents Leptonic, semileptonic & radiative decays Rare decays Bottom mesons Hadron colliders

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Hard color-singlet exchange in dijet events in proton-proton collisions at s=13 TeV

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Physical Review D 2021年第3期104卷 032009-032009页

作者： A. M. Sirunyan A. Tumasyan W. Adam F. Ambrogi T. Bergauer M. Dragicevic J. Erö A. Escalante Del Valle R. Frühwirth M. Jeitler N. Krammer L. Lechner D. Liko T. Madlener I. Mikulec F. M. Pitters N. Rad J. Schieck R. Schöfbeck M. Spanring S. Templ W. Waltenberger C.-E. Wulz M. Zarucki V. Chekhovsky A. Litomin V. Makarenko J. Suarez Gonzalez M. R. Darwish E. A. De Wolf D. Di Croce X. Janssen T. Kello A. Lelek M. Pieters H. Rejeb Sfar H. Van Haevermaet P. Van Mechelen S. Van Putte N. Van Remortel F. Blekman E. S. Bols S. S. Chhibra J. D’Hondt J. De Clercq D. Lontkovskyi S. Lowette I. Marchesini S. Moortgat A. Morton Q. Python S. Tavernier W. Van Doninck P. Van Mulders D. Beghin B. Bilin B. Clerbaux G. De Lentdecker H. Delannoy B. Dorney L. Favart A. Grebenyuk A. K. Kalsi I. Makarenko L. Moureaux L. Pétré A. Popov N. Postiau E. Starling L. Thomas C. Vander Velde P. Vanlaer D. Vannerom L. Wezenbeek T. Cornelis D. Dobur M. Gruchala I. Khvastunov M. Niedziela C. Roskas K. Skovpen M. Tytgat W. Verbeke B. Vermassen M. Vit G. Bruno F. Bury C. Caputo P. David C. Delaere M. Delcourt I. S. Donertas A. Giammanco V. Lemaitre K. Mondal J. Prisciandaro A. Taliercio M. Teklishyn P. Vischia S. Wuyckens J. Zobec G. A. Alves G. Correia Silva C. Hensel A. Moraes W. L. Aldá Júnior E. Belchior Batista Das Chagas H. Brandao Malbouisson W. Carvalho J. Chinellato E. Coelho E. M. Da Costa G. G. Da Silveira D. De Jesus Damiao S. Fonseca De Souza J. Martins D. Matos Figueiredo M. Medina Jaime M. Melo De Almeida C. Mora Herrera L. Mundim H. Nogima P. Rebello Teles L. J. Sanchez Rosas A. Santoro S. M. Silva Do Amaral A. Sznajder M. Thiel E. J. Tonelli Manganote F. Torres Da Silva De Araujo A. Vilela Pereira C. A. Bernardes L. Calligaris T. R. Fernandez Perez Tomei E. M. Gregores D. S. Lemos P. G. Mercadante S. F. Novaes Sandra S. Padula A. Aleksandrov R. Hadjiiska P. Iaydjiev M. Misheva M. Rodozov M. Shopova G. Sultanov M. Bonchev A. Dimitrov T. Ivanov L. Litov B. Pavlov P. Petkov A. Petrov W. Fang Q. Guo H. Wang L. Yuan M. Ahmad Z. Hu Y. Wang E. 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 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 University of Illinois at Chicago (UIC) Chicago Illinois USA Department of Physics Tsinghua University Beijing China University of Virginia Charlottesville Virginia USA Institute of High Energy Physics Beijing China Massachusetts Institute of Technology Cambridge Massachusetts USA State Key Laboratory of Nuclear Physics and Technology Peking University Beijing China The University of Kansas Lawrence Kansas USA Sun Yat-Sen University Guangzhou China Institute of Modern Physics and Key Laboratory of Nuclear Physics and Ion-beam Application (MOE)—Fudan University Shanghai China Zhejiang University Hangzhou China Universidad de Los Andes Bogota Colombia Universidad de Antioquia Medellin 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 Center for High Energy Physic

Events where the two leading jets are separated by a pseudorapidity interval devoid of particle activity, known as jet-gap-jet events, are studied in proton-proton collisions at s=13 TeV. The signature is expected from hard color-singlet exchange. Each of the highest transverse momentum (pT) jets must have pTjet>40 GeV and pseudorapidity 1.4<|ηjet|<4.7, with ηjet1ηjet2<0, where jet1 and jet2 are the leading and subleading jets in pT, respectively. The analysis is based on data collected by the CMS and TOTEM experiments during a low luminosity, high-β* run at the CERN LHC in 2015, with an integrated luminosity of 0.66 pb−1. Events with a low number of charged particles with pT>0.2 GeV in the interval |η|<1 between the jets are observed in excess of calculations that assume only color-exchange. The fraction of events produced via color-singlet exchange, fCSE, is measured as a function of pTjet2, the pseudorapidity difference between the two leading jets, and the azimuthal angular separation between the two leading jets. The fraction fCSE has values of 0.4–1.0%. The results are compared with previous measurements and with predictions from perturbative quantum chromodynamics. In addition, the first study of jet-gap-jet events detected in association with an intact proton using a subsample of events with an integrated luminosity of 0.40 pb−1 is presented. The intact protons are detected with the Roman pot detectors of the TOTEM experiment. The fCSE in this sample is 2.91±0.70(stat)−1.01+1.08(syst) times larger than that for inclusive dijet production in dijets with similar kinematics.

关键词： Quark & gluon jets Hadron colliders

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Detecting haplotype amplification in cancer sequencing data 9

Detecting haplotype amplification in cancer sequencing data

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9th International Conference on Bioinformatics and Computational Biology, BICOB 2017

作者： Liu, Weiwei Gao, Jingyang Zhao, Zhongmeng Yang, Rongrong Geng, Yu Zheng, Tian Zhang, Xuanping Xiao, Xiao Wang, Jiayin College of Information Science and Technology Beijing University of Chemical Technology 15 East Beisanhuan Road Beijing China Department of Computer Science and Technology Xi'an Jiaotong University 28 West Xianning Road Xi'an China Shaanxi Engineering Research Center of Medical and Health Big Data Xi'an Jiaotong University 28 West Xianning Road Xi'an China School of Management Xi'an Jiaotong University 28 West Xianning Road Xi'an China Institute of Data Science and Information Quality Xi'an Jiaotong University 28 West Xianning Road Xi'an China

ISBN: (纸本)9781943436071

Haplotype amplification on germline variants often implies selective advantage and clonal expansion susceptibility. Efficiently and accurately estimating such amplification provides insights into tumour heterogeneity and clinical implications. Existing approaches on amplification detecting are either limited on array data or focusing on genotype level only, whose accuracy may often be hurt by read depth bias or coverage deviation in clinical sequencing. In this article, we propose HMMLD, a computational approach for haplotype amplification detection. This approach is implemented based on a hidden Markov framework. Both read depth and variant allelic frequency are modeled as observed variables, while the hidden states are mapped to unknown amplifications. As we are considering germline variants, this approach involves linkage disequilibrium and interactions between germline loci, which improves accuracy by maximizing the posterior likelihoods on observed variables. We test HMMLD, on both simulation datasets with different configurations and a set of TCGA paired sequencing samples. The results outperform the existing approaches, especially on low coverage regions.

关键词： Bioinformatics

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Investigating how well contextual features are captured by bi-directional recurrent neural network models

arXiv

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arXiv 2017年

作者： Chawla, Kushal Sahu, Sunil Kumar Anand, Ashish Adobe Research Big Data Experience Lab BangaloreKarnataka India National Center for Text Mining University of Manchester United Kingdom Department of Computer Science and Engineering IIT GuwahatiAssam India

Learning algorithms for natural language processing (NLP) tasks traditionally rely on manually defined relevant contextual features. On the other hand, neural network models using an only distributional representation of words have been successfully applied for several NLP tasks. Such models learn features automatically and avoid explicit feature engineering. Across several domains, neural models become a natural choice specifically when limited characteristics of data are known. However, this flexibility comes at the cost of interpretability. In this paper, we define three different methods to investigate ability of bi-directional recurrent neural networks (RNNs) in capturing contextual features. In particular, we analyze RNNs for sequence tagging tasks. We perform a comprehensive analysis on general as well as biomedical domain datasets. Our experiments focus on important contextual words as features, which can easily be extended to analyze various other feature types. We also investigate positional effects of context words and show how the developed methods can be used for error analysis. Copyright © 2017, The Authors. All rights reserved.

关键词： Recurrent neural networks

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Search for resonances in fully hadronic final states in pp collisions at = 13 TeV with the ATLAS detector

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Journal of High Energy Physics 2020年第10期2020卷 1-43页

作者： Aad, G. Abbott, B. Abbott, D. C. Abed Abud, A. Abeling, K. Abhayasinghe, D. K. Abidi, S. H. AbouZeid, O. S. Abraham, N. L. Abramowicz, H. Abreu, H. Abulaiti, Y. Acharya, B. S. Achkar, B. Adam, L. Adam Bourdarios, C. Adamczyk, L. Adamek, L. Adelman, J. Adersberger, M. Adiguzel, A. Adorni, S. Adye, T. Affolder, A. A. Afik, Y. Agapopoulou, C. Agaras, M. N. Aggarwal, A. Agheorghiesei, C. Aguilar-Saavedra, J. A. Ahmad, A. Ahmadov, F. Ahmed, W. S. ai, X. aielli, G. Akatsuka, S. Åkesson, T. P. A. Akilli, E. Akimov, A. V. Al Khoury, K. Alberghi, G. L. Albert, J. Alconada Verzini, M. J. Alderweireldt, S. Aleksa, M. Aleksandrov, I. N. Alexa, C. Alexopoulos, T. Alfonsi, A. Alfonsi, F. Alhroob, M. Ali, B. Ali, S. Aliev, M. Alimonti, G. Allaire, C. Allbrooke, B. M. M. Allen, B. W. Allport, P. P. Aloisio, A. Alonso, F. Alpigiani, C. Alunno Camelia, E. Alvarez Estevez, M. Alviggi, M. G. Amaral Coutinho, Y. Ambler, A. Ambroz, L. Amelung, C. Amidei, D. Amor Dos Santos, S. P. Amoroso, S. Amrouche, C. S. An, F. Anastopoulos, C. Andari, N. Andeen, T. Anders, J. K. Andrean, S. Y. Andreazza, A. Andrei, V. Anelli, C. R. Angelidakis, S. Angerami, A. Anisenkov, A. V. Annovi, A. Antel, C. Anthony, M. T. Antipov, E. Antonelli, M. Antrim, D. J. A. Anulli, F. Aoki, M. Aparisi Pozo, J. A. Aparo, M. A. Aperio Bella, L. Aranzabal Barrio, N. Araujo Ferraz, V. Araujo Pereira, R. Arcangeletti, C. Arce, A. T. H. Arduh, F. A. Arguin, J-F. Argyropoulos, S. Arling, J.-H. Armbruster, A. J. Armstrong, A. Arnaez, O. Arnold, H. Arrubarrena Tame, Z. P. Artoni, G. Asai, K. Asai, S. Asawatavonvanich, T. Asbah, N. Asimakopoulou, E. M. Asquith, L. Assahsah, J. Assamagan, K. Astalos, R. Atkin, R. J. Atkinson, M. Atlay, N. B. Atmani, H. Augsten, K. Austrup, V. A. Avolio, G. Ayoub, M. K. Azuelos, G. Bachacou, H. Bachas, K. Backes, M. Backman, F. Bagnaia, P. Bahmani, M. Bahrasemani, H. Bailey, A. J. Bailey, V. R. Baines, J. T. Bakalis, C. Baker, O. K. Bakker, P. J. Bakos, E. Bakshi Gupta, D. Balaji, S. Baldin, E. M. Balek, P. Balli, F. Balunas, W. K. Balz, J. Bana CPPM Aix-Marseille Université CNRS/IN2P3 Marseille France Homer L. Dodge Department of Physics and Astronomy University of Oklahoma Norman United States of America Department of Physics University of Massachusetts Amherst United States of America CERN Geneva Switzerland II. Physikalisches Institut Georg-August-Universität Göttingen Göttingen Germany Department of Physics Royal Holloway University of London Egham United Kingdom Department of Physics University of Toronto Toronto Canada Niels Bohr Institute University of Copenhagen Copenhagen Denmark 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 High Energy Physics Division Argonne National Laboratory Argonne United States of America INFN Gruppo Collegato di Udine Sezione di Trieste Udine Italy ICTP Trieste Italy Department of Physics King’s College London London United Kingdom Institut für Physik Universität Mainz Mainz Germany LAPP Université Grenoble Alpes Université Savoie Mont Blanc CNRS/IN2P3 Annecy France AGH University of Science and Technology Faculty of Physics and Applied Computer Science Krakow Poland Department of Physics Northern Illinois University DeKalb United States of America Fakultät für Physik Ludwig-Maximilians-Universität München München Germany Department of Physics Bogazici University Istanbul Turkey Département de Physique Nucléaire et Corpusculaire Université de Genève Genève Switzerland Particle Physics Department Rutherford Appleton Laboratory Didcot United Kingdom Santa Cruz Institute for Particle Physics University of California Santa Cruz Santa Cruz United States of America IJCLab Université Paris-Saclay CNRS/IN2P3 Orsay France LPC Université Clermont Auvergne CNRS/IN2P3 Clermont-Ferrand France Institute for Mathematics Astrophysics and Particle Phys

This paper presents a search for new heavy particles decaying into a pair of top quarks using 139 fb−1 of proton-proton collision data recorded at a centre-of-mass energy of $$ \sqrt{s} $$ = 13 TeV with the ATLAS detector at the Large Hadron Collider. The search is performed using events consistent with pair production of high-transverse-momentum top quarks and their subsequent decays into the fully hadronic final states. The analysis is optimized for resonances decaying into a $$ t\overline{t} $$ pair with mass above 1.4 TeV, exploiting a dedicated multivariate technique with jet substructure to identify hadronically decaying top quarks using large-radius jets and evaluating the background expectation from data. No significant deviation from the background prediction is observed. Limits are set on the production cross-section times branching fraction for the new Z′ boson in a topcolor-assisted-technicolor model. The Z′ boson masses below 3.9 and 4.7 TeV are excluded at 95% confidence level for the decay widths of 1% and 3%, respectively.

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Search for long-lived particles decaying to jets with displaced vertices in proton-proton collisions at s=13 TeV

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Physical Review D 2021年第5期104卷 052011-052011页

作者： A. M. Sirunyan A. Tumasyan W. Adam T. Bergauer M. Dragicevic A. Escalante Del Valle R. Frühwirth M. Jeitler N. Krammer L. Lechner D. Liko I. Mikulec F. M. Pitters J. Schieck R. Schöfbeck M. Spanring S. Templ W. Waltenberger C.-E. Wulz M. Zarucki V. Chekhovsky A. Litomin V. Makarenko M. R. Darwish E. A. De Wolf X. Janssen T. Kello A. Lelek H. Rejeb Sfar P. Van Mechelen S. Van Putte N. Van Remortel F. Blekman E. S. Bols J. D’Hondt J. De Clercq S. Lowette S. Moortgat A. Morton D. Müller A. R. Sahasransu S. Tavernier W. Van Doninck P. Van Mulders D. Beghin B. Bilin B. Clerbaux G. De Lentdecker B. Dorney L. Favart A. Grebenyuk A. K. Kalsi K. Lee I. Makarenko L. Moureaux L. Pétré A. Popov N. Postiau E. Starling L. Thomas C. Vander Velde P. Vanlaer D. Vannerom L. Wezenbeek T. Cornelis D. Dobur M. Gruchala I. Khvastunov G. Mestdach M. Niedziela C. Roskas K. Skovpen M. Tytgat W. Verbeke B. Vermassen M. Vit A. Bethani G. Bruno F. Bury C. Caputo P. David C. Delaere M. Delcourt I. S. Donertas A. Giammanco V. Lemaitre K. Mondal J. Prisciandaro A. Taliercio M. Teklishyn P. Vischia S. Wertz S. Wuyckens G. A. Alves C. Hensel A. Moraes W. L. Aldá Júnior E. Belchior Batista Das Chagas H. Brandao Malbouisson W. Carvalho J. Chinellato E. Coelho E. M. Da Costa G. G. Da Silveira D. De Jesus Damiao S. Fonseca De Souza J. Martins D. Matos Figueiredo C. Mora Herrera L. Mundim H. Nogima P. Rebello Teles L. J. Sanchez Rosas A. Santoro S. M. Silva Do Amaral A. Sznajder M. Thiel F. Torres Da Silva De Araujo A. Vilela Pereira C. A. Bernardes L. Calligaris T. R. Fernandez Perez Tomei E. M. Gregores D. S. Lemos P. G. Mercadante S. F. Novaes Sandra S. Padula A. Aleksandrov G. Antchev I. Atanasov R. Hadjiiska P. Iaydjiev M. Misheva M. Rodozov M. Shopova G. Sultanov A. Dimitrov T. Ivanov L. Litov B. Pavlov P. Petkov A. Petrov T. Cheng W. Fang Q. Guo M. Mittal H. Wang L. Yuan M. Ahmad G. Bauer Z. Hu Y. Wang K. Yi E. Chapon G. M. Chen H. S. Chen M. Chen T. Javaid A. Kapoor D. Leggat H. Liao Z.-A. Liu R. Sharma A. Spiezia J. Tao J. Thomas-Wilsker J. 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 Korea University Seoul Korea 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 Rutgers The State University of New Jersey Piscataway New Jersey USA Department of Physics Tsinghua University Beijing China Institute of High Energy Physics Beijing China Massachusetts Institute of Technology Cambridge Massachusetts USA State Key Laboratory of Nuclear Physics and Technology Peking University Beijing China The University of Kansas Lawrence Kansas USA Sun Yat-Sen University Guangzhou China Institute of Modern Physics and Key Laboratory of Nuclear Physics and Ion-beam Application (MOE)—Fudan University Shanghai China Zhejiang University Hangzhou China Universidad de Los Andes Bogota Colombia Universidad de Antioquia Medellin 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 Center for High Energy Physics (CHEP-FU) Fa

A search is presented for long-lived particles produced in pairs in proton-proton collisions at the LHC operating at a center-of-mass energy of 13 TeV. The data were collected with the CMS detector during the period from 2015 through 2018, and correspond to a total integrated luminosity of 140 fb−1. This search targets pairs of long-lived particles with mean proper decay lengths between 0.1 and 100 mm, each of which decays into at least two quarks that hadronize to jets, resulting in a final state with two displaced vertices. No significant excess of events with two displaced vertices is observed. In the context of R-parity violating supersymmetry models, the pair production of long-lived neutralinos, gluinos, and top squarks is excluded at 95% confidence level for cross sections larger than 0.08 fb, masses between 800 and 3000 GeV, and mean proper decay lengths between 1 and 25 mm.

关键词： Hypothetical particle physics models Supersymmetric models Hadron colliders

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First Observation of the Decay Bs0→K−μ+νμ and a Measurement of |Vub|/|Vcb|

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Physical Review Letters 2021年第8期126卷 081804-081804页

作者： R. Aaij C. Abellán Beteta T. Ackernley B. Adeva M. Adinolfi H. Afsharnia C. A. aidala S. aiola Z. Ajaltouni S. Akar J. Albrecht F. Alessio M. Alexander A. Alfonso Albero Z. Aliouche G. Alkhazov P. Alvarez Cartelle S. Amato Y. Amhis L. An L. Anderlini A. Andreianov M. Andreotti F. Archilli A. Artamonov M. Artuso K. Arzymatov E. Aslanides M. Atzeni B. Audurier S. Bachmann M. Bachmayer J. J. Back S. Baker P. Baladron Rodriguez V. Balagura W. Baldini J. Baptista Leite R. J. Barlow S. Barsuk W. Barter M. Bartolini F. Baryshnikov J. M. Basels G. Bassi B. Batsukh A. Battig A. Bay M. Becker F. Bedeschi I. Bediaga A. Beiter V. Belavin S. Belin V. Bellee K. Belous I. Belov I. Belyaev G. Bencivenni E. Ben-Haim A. Berezhnoy R. Bernet D. Berninghoff H. C. Bernstein C. Bertella E. Bertholet A. Bertolin C. Betancourt F. Betti M. O. Bettler Ia. Bezshyiko S. Bhasin J. Bhom L. Bian M. S. Bieker S. Bifani P. Billoir M. Birch F. C. R. Bishop A. Bizzeti M. Bjørn M. P. Blago T. Blake F. Blanc S. Blusk D. Bobulska J. A. Boelhauve O. Boente Garcia T. Boettcher A. Boldyrev A. Bondar N. Bondar S. Borghi M. Borisyak M. Borsato J. T. Borsuk S. A. Bouchiba T. J. V. Bowcock A. Boyer C. Bozzi M. J. Bradley S. Braun A. Brea Rodriguez M. Brodski J. Brodzicka A. Brossa Gonzalo D. Brundu A. Buonaura C. Burr A. Bursche A. Butkevich J. S. Butter J. Buytaert W. Byczynski S. Cadeddu H. Cai R. Calabrese L. Calefice L. Calero Diaz S. Cali R. Calladine M. Calvi M. Calvo Gomez P. Camargo Magalhaes A. Camboni P. Campana D. H. Campora Perez A. F. Campoverde Quezada S. Capelli L. Capriotti A. Carbone G. Carboni R. Cardinale A. Cardini I. Carli P. Carniti L. Carus K. Carvalho Akiba A. Casais Vidal G. Casse M. Cattaneo G. Cavallero S. Celani J. Cerasoli A. J. Chadwick M. G. Chapman M. Charles Ph. Charpentier G. Chatzikonstantinidis C. A. Chavez Barajas M. Chefdeville C. Chen S. Chen A. Chernov S.-G. Chitic V. Chobanova S. Cholak M. Chrzaszcz A. Chubykin V. Chulikov P. Ciambrone M. F. Cicala X. Cid Vidal G. Ciezarek P. E. L. Clarke M. Clemencic H. V. Cliff J. C Nikhef National Institute for Subatomic Physics Amsterdam Netherlands Physik-Institut Universität Zürich Zürich Switzerland Oliver Lodge Laboratory University of Liverpool Liverpool United Kingdom Instituto Galego de Física de Altas Enerxías (IGFAE) Universidade de Santiago de Compostela Santiago de Compostela Spain H.H. Wills Physics Laboratory University of Bristol Bristol United Kingdom Université Clermont Auvergne CNRS/IN2P3 LPC Clermont-Ferrand France University of Michigan Ann Arbor Michigan USA (associated with Syracuse University Syracuse New York USA) INFN Sezione di Milano Milano Italy University of Cincinnati Cincinnati Ohio USA Fakultät Physik Technische Universität Dortmund Dortmund Germany European Organization for Nuclear Research (CERN) Geneva Switzerland School of Physics and Astronomy University of Glasgow Glasgow United Kingdom ICCUB Universitat de Barcelona Barcelona Spain Department of Physics and Astronomy University of Manchester Manchester United Kingdom Petersburg Nuclear Physics Institute NRC Kurchatov Institute (PNPI NRC KI) Gatchina Russia Universidade Federal do Rio de Janeiro (UFRJ) Rio de Janeiro Brazil Université Paris-Saclay CNRS/IN2P3 IJCLab Orsay France INFN Sezione di Firenze Firenze Italy INFN Sezione di Ferrara Ferrara Italy Physikalisches Institut Ruprecht-Karls-Universität Heidelberg Heidelberg Germany Institute for High Energy Physics NRC Kurchatov Institute (IHEP NRC KI) Protvino Russia Protvino Russia Syracuse University Syracuse New York USA Yandex School of Data Analysis Moscow Russia Aix Marseille Univ CNRS/IN2P3 CPPM Marseille France Laboratoire Leprince-ringuet (llr) Palaiseau France Institute of Physics Ecole Polytechnique Fédérale de Lausanne (EPFL) Lausanne Switzerland Department of Physics University of Warwick Coventry United Kingdom Imperial College London London United Kingdom Centro Brasileiro de Pesquisas Físicas (CBPF) Rio de Janeiro Brazil INFN Sezione di Genova Genova It

The first observation of the suppressed semileptonic Bs0→K−μ+νμ decay is reported. Using a data sample recorded in pp collisions in 2012 with the LHCb detector, corresponding to an integrated luminosity of 2 fb−1, the branching fraction B(Bs0→K−μ+νμ) is measured to be [1.06±0.05(stat)±0.08(syst)]×10−4, where the first uncertainty is statistical and the second one represents the combined systematic uncertainties. The decay Bs0→Ds−μ+νμ, where Ds− is reconstructed in the final state K+K−π−, is used as a normalization channel to minimize the experimental systematic uncertainty. Theoretical calculations on the form factors of the Bs0→K− and Bs0→Ds− transitions are employed to determine the ratio of the Cabibbo-Kobayashi-Maskawa matrix elements |Vub|/|Vcb| at low and high Bs0→K− momentum transfer.

关键词： Branching fraction Form factors Leptonic, semileptonic & radiative decays Particle decays

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