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Amplitude analysis of the B+→π+π+π− decay

Physical Review D 2020年第1期101卷 012006-012006页

作者： R. Aaij C. Abellán Beteta B. Adeva M. Adinolfi C. A. Aidala Z. Ajaltouni S. Akar P. Albicocco J. Albrecht F. Alessio M. Alexander A. Alfonso Albero G. Alkhazov P. Alvarez Cartelle A. A. Alves, Jr. S. Amato Y. Amhis L. An L. Anderlini G. Andreassi M. Andreotti J. E. Andrews F. Archilli J. Arnau Romeu A. Artamonov M. Artuso K. Arzymatov E. Aslanides M. Atzeni B. Audurier S. Bachmann J. J. Back S. Baker V. Balagura W. Baldini A. Baranov R. J. Barlow S. Barsuk W. Barter M. Bartolini F. Baryshnikov V. Batozskaya B. Batsukh A. Battig V. Battista A. Bay F. Bedeschi I. Bediaga A. Beiter L. J. Bel V. Belavin S. Belin N. Beliy V. Bellee K. Belous I. Belyaev G. Bencivenni E. Ben-Haim S. Benson S. Beranek A. Berezhnoy R. Bernet D. Berninghoff E. Bertholet A. Bertolin C. Betancourt F. Betti M. O. Bettler Ia. Bezshyiko S. Bhasin J. Bhom M. S. Bieker S. Bifani P. Billoir A. Birnkraut A. Bizzeti M. Bjørn M. P. Blago T. Blake F. Blanc S. Blusk D. Bobulska V. Bocci O. Boente Garcia T. Boettcher A. Boldyrev A. Bondar N. Bondar S. Borghi M. Borisyak M. Borsato M. Boubdir T. J. V. Bowcock C. Bozzi S. Braun A. Brea Rodriguez M. Brodski J. Brodzicka A. Brossa Gonzalo D. Brundu E. Buchanan A. Buonaura C. Burr A. Bursche J. S. Butter J. Buytaert W. Byczynski S. Cadeddu H. Cai R. Calabrese S. Cali R. Calladine M. Calvi M. Calvo Gomez P. Camargo Magalhaes A. Camboni P. Campana D. H. Campora Perez L. Capriotti A. Carbone G. Carboni R. Cardinale A. Cardini P. Carniti K. Carvalho Akiba A. Casais Vidal G. Casse M. Cattaneo G. Cavallero R. Cenci M. G. Chapman M. Charles Ph. Charpentier G. Chatzikonstantinidis M. Chefdeville V. Chekalina C. Chen S. Chen S.-G. Chitic V. Chobanova M. Chrzaszcz A. Chubykin P. Ciambrone X. Cid Vidal G. Ciezarek F. Cindolo P. E. L. Clarke M. Clemencic H. V. Cliff J. Closier J. L. Cobbledick V. Coco J. A. B. Coelho J. Cogan E. Cogneras L. Cojocariu P. Collins T. Colombo A. Comerma-Montells A. Contu G. Coombs S. Coquereau G. Corti C. M. Costa Sobral B. Couturier G. A. Cowan D. C. Craik A. Crocombe M. Cruz Torres R. Cur Nikhef National Institute for Subatomic Physics Amsterdam Netherlands Physik-Institut Universität Zürich Zürich Switzerland 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 University of Michigan Ann Arbor USA (associated with Syracuse University Syracuse New york USA) Université Clermont Auvergne CNRS/IN2P3 LPC Clermont-Ferrand France University of Cincinnati Cincinnati Ohio USA INFN Laboratori Nazionali di Frascati Frascati Italy 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 Petersburg Nuclear Physics Institute NRC Kurchatov Institute (PNPI NRC KI) Gatchina Russia Imperial College London London United Kingdom Universidade Federal do Rio de Janeiro (UFRJ) Rio de Janeiro Brazil LAL Univ. Paris-Sud CNRS/IN2P3 Université Paris-Saclay Orsay France INFN Sezione di Firenze Firenze Italy Institute of Physics Ecole Polytechnique Fédérale de Lausanne (EPFL) Lausanne Switzerland INFN Sezione di Ferrara Ferrara Italy University of Maryland College Park Maryland USA Aix Marseille Univ CNRS/IN2P3 CPPM Marseille France 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 INFN Sezione di Cagliari Monserrato Italy Physikalisches Institut Ruprecht-Karls-Universität Heidelberg Heidelberg Germany Department of Physics University of Warwick Coventry United Kingdom School of Physics and Astronomy University of Manchester Manchester United Kingdom INFN Sezione di Genova Genova Italy National Center for Nuclear Research (NCBJ) Warsaw Poland INFN Sezione di Pisa P

The results of an amplitude analysis of the charmless three-body decay B+→π+π+π−, in which CP-violation effects are taken into account, are reported. The analysis is based on a data sample corresponding to an integrated luminosity of 3 fb−1 of pp collisions recorded with the LHCb detector. The most challenging aspect of the analysis is the description of the behavior of the π+π− S-wave contribution, which is achieved by using three complementary approaches based on the isobar model, the K-matrix formalism, and a quasi-model-independent procedure. Additional resonant contributions for all three methods are described using a common isobar model, and include the ρ(770)0, ω(782) and ρ(1450)0 resonances in the π+π− P-wave, the f2(1270) resonance in the π+π− D-wave, and the ρ3(1690)0 resonance in the π+π− F-wave. Significant CP-violation effects are observed in both S- and D-waves, as well as in the interference between the S- and P-waves. The results from all three approaches agree and provide new insight into the dynamics and the origin of CP-violation effects in B+→π+π+π− decays.

关键词： Hadronic decays Bottom mesons CP violation Hadron colliders

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Correction to: Constraint-based causal discovery with mixed data

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International Journal of data science and Analytics 2018年第1期6卷 31-31页

作者： Michail Tsagris Giorgos Borboudakis Vincenzo Lagani Ioannis Tsamardinos Department of Computer Science University of Crete Heraklion Greece Gnosis Data Analysis (Gnosis DA) University of Crete Heraklion Greece Institute of Applied and Computational Mathematics Foundation for Research and Technology Hellas Greece

The article “Constraint-based causal discovery with mixed data,” written by Michail Tsagris, Giorgos Borboudakis, Vincenzo Lagani, and Ioannis Tsamardinos, was originally published electronically on the publisher’s...

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Inductive conformal martingales for change-point detection

arXiv

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arXiv 2017年

作者： Volkhonskiy, Denis Burnaev, Evgeny Nouretdinov, Ilia Gammerman, Alexander Vovk, Vladimir Yandex School of Data Analysis Moscow Russia Skolkovo Institute of Science and Technology Skolkovo Moscow Region Russia Institute for Information Transmission Problems Moscow Russia Information Security Group and Computer Learning Research Center Department of Computer Science Royal Holloway University of London London United Kingdom Computer Learning Research Center Department of Computer Science Royal Holloway University of London London United Kingdom

We consider the problem of quickest change-point detection in data streams. Classical change-point detection procedures, such as CUSUM, Shiryaev-Roberts and Posterior Probability statistics, are optimal only if the change-point model is known, which is an unrealistic assumption in typical applied problems. Instead we propose a new method for change-point detection based on Inductive Conformal Martingales, which requires only the independence and identical distribution of observations. We compare the proposed approach to standard methods, as well as to change-point detection oracles, which model a typical practical situation when we have only imprecise (albeit parametric) information about pre- and post-change data distributions. Results of comparison provide evidence that change-point detection based on Inductive Conformal Martingales is an efficient tool, capable to work under quite general conditions unlike traditional approaches. Copyright © 2017, The Authors. All rights reserved.

关键词： Anomaly detection

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DCAR: A Discriminative and Compact Audio Representation for Audio Processing

DCAR: A Discriminative and Compact Audio Representation for ...

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作者： Jing, Liping Liu, Bo Choi, Jaeyoung Janin, Adam Bernd, Julia Mahoney, Michael W. Friedland, Gerald Beijing Key Laboratory of Traffic Data Analysis and Mining Beijing Jiaotong University Beijing100044 China College of Information Science and Technology Agricultural University of Hebei Hebei071000 China International Computer Science Institute BerkeleyCA94704 United States Delft University of Technology Delft2628 Netherlands Department of Statistics University of California Berkeley BerkeleyCA94720 United States Department of Electrical Engineering and Computer Sciences University of California Berkeley BerkeleyCA94720 United States Lawrence Livermore National Laboratory LivermoreCA94550 United States

This paper presents a novel two-phase method for audio representation, discriminative and compact audio representation (DCAR), and evaluates its performance at detecting events and scenes in consumer-produced videos. In the first phase of DCAR, each audio track is modeled using a Gaussian mixture model (GMM) that includes several components to capture the variability within that track. The second phase takes into account both global structure and local structure. In this phase, the components are rendered more discriminative and compact by formulating an optimization problem on a Grassmannian manifold. The learned components can effectively represent the structure of audio. Our experiments used the YLI-MED and DCASE Acoustic Scenes datasets. The results show that variants on the proposed DCAR representation consistently outperform four popular audio representations (mv-vector, i-vector, GMM, and HEM-GMM). The advantage is significant for both easier and harder discrimination tasks;we discuss how these performance differences across tasks follow from how each type of model leverages (or does not leverage) the intrinsic structure of the data. © 2017 IEEE.

关键词： Gaussian distribution

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Erratum to: Study of ϒ production in pPb collisions at = 8.16 TeV

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Journal of High Energy Physics 2020年第2期2020卷 1-8页

作者： Aaij, R. Abellán Beteta, C. Adeva, B. Adinolfi, M. Aidala, C. A. Ajaltouni, Z. Akar, S. Albicocco, P. Albrecht, J. Alessio, F. Alexander, M. Alfonso Albero, A. Alkhazov, G. Alvarez Cartelle, P. Alves, A. A. Amato, S. Amerio, S. Amhis, Y. An, L. Anderlini, L. Andreassi, G. Andreotti, M. Andrews, J. E. Appleby, R. B. Archilli, F. d’Argent, P. Arnau Romeu, J. Artamonov, A. Artuso, M. Arzymatov, K. Aslanides, E. Atzeni, M. Audurier, B. Bachmann, S. Back, J. J. Baker, S. Balagura, V. Baldini, W. Baranov, A. Barlow, R. J. Barsuk, S. Barter, W. Bartolini, M. Baryshnikov, F. Batozskaya, V. Batsukh, B. Battig, A. Battista, V. Bay, A. Beddow, J. Bedeschi, F. Bediaga, I. Beiter, A. Bel, L. J. Belin, S. Beliy, N. Bellee, V. Belloli, N. Belous, K. Belyaev, I. Ben-Haim, E. Bencivenni, G. Benson, S. Beranek, S. Berezhnoy, A. Bernet, R. Berninghoff, D. Bertholet, E. Bertolin, A. Betancourt, C. Betti, F. Bettler, M. O. van Beuzekom, M. Bezshyiko, Ia. Bhasin, S. Bhom, J. Bifani, S. Billoir, P. Birnkraut, A. Bizzeti, A. Bjørn, M. Blago, M. P. Blake, T. Blanc, F. Blusk, S. Bobulska, D. Bocci, V. Boente Garcia, O. Boettcher, T. Bondar, A. Bondar, N. Borghi, S. Borisyak, M. Borsato, M. Bossu, F. Boubdir, M. Bowcock, T. J. V. Bozzi, C. Braun, S. Brodski, M. Brodzicka, J. Brossa Gonzalo, A. Brundu, D. Buchanan, E. Buonaura, A. Burr, C. Bursche, A. Buytaert, J. Byczynski, W. Cadeddu, S. Cai, H. Calabrese, R. Calladine, R. Calvi, M. Calvo Gomez, M. Camboni, A. Campana, P. Campora Perez, D. H. Capriotti, L. Carbone, A. Carboni, G. Cardinale, R. Cardini, A. Carniti, P. Carson, L. Carvalho Akiba, K. Casse, G. Cassina, L. Cattaneo, M. Cavallero, G. Cenci, R. Chamont, D. Chapman, M. G. Charles, M. Charpentier, Ph. Chatzikonstantinidis, G. Chefdeville, M. Chekalina, V. Chen, C. Chen, S. Chitic, S.-G. Chobanova, V. Chrzaszcz, M. Chubykin, A. Ciambrone, P. Cid Vidal, X. Ciezarek, G. Clarke, P. E. L. Clemencic, M. Cliff, H. V. Closier, J. Coco, V. Coelho, J. A. B. Cogan, J. Cogneras, E. Cojocariu, L. Collins, P. Colombo, T. Comerma-Montells, A. Co Nikhef National Institute for Subatomic Physics Amsterdam Netherlands Physik-Institut Universität Zürich Zürich Switzerland 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 University of Michigan Ann Arbor United States Clermont Université Université Blaise Pascal CNRS/IN2P3 LPC Clermont-Ferrand France University of Cincinnati Cincinnati United States INFN Laboratori Nazionali di Frascati Frascati Italy 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 Petersburg Nuclear Physics Institute (PNPI) Gatchina Russia Imperial College London London United Kingdom Universidade Federal do Rio de Janeiro (UFRJ) Rio de Janeiro Brazil INFN Sezione di Padova Padova Italy LAL Univ. Paris-Sud CNRS/IN2P3 Université Paris-Saclay Orsay France Center for High Energy Physics Tsinghua University Beijing China INFN Sezione di Firenze Firenze Italy Institute of Physics Ecole Polytechnique Fédérale de Lausanne (EPFL) Lausanne Switzerland INFN Sezione di Ferrara Ferrara Italy University of Maryland College Park United States School of Physics and Astronomy University of Manchester Manchester United Kingdom Physikalisches Institut Ruprecht-Karls-Universität Heidelberg Heidelberg Germany Aix Marseille Univ CNRS/IN2P3 CPPM Marseille France Institute for High Energy Physics (IHEP) Protvino Russia Syracuse University Syracuse United States Yandex School of Data Analysis Moscow Russia INFN Sezione di Cagliari Monserrato Italy Department of Physics University of Warwick Coventry United Kingdom Laboratoire Leprince-Ringuet Palaiseau France INFN Sezione di Genova Genova Italy National University of Science and Techno

In figure 11 of the original paper.

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Introducing evolutionary biologists to the analysis of big data: Guidelines to organize extended bioinformatics training courses

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Evolution: Education and Outreach 2018年第1期11卷 1-10页

作者： Faria, Rui Triant, Deborah Perdomo-Sabogal, Alvaro Overduin, Bert Bleidorn, Christoph Santana, Clara Isabel Bermudez Langenberger, David Indrischek, Henrike Aerts, Jan Engelhardt, Jan Engelken, Johannes Liebal, Katja Fasold, Mario Robb, Sofia Grath, Sonja Kolora, Sree Rohit Raj Carvalho, Tiago Salzburger, Walter Jovanovic, Vladimir Nowick, Katja CIBIO Centro de Investigação em Biodiversidade e Recursos Genéticos InBIO Laboratório Associado Universidade Do Porto Campus Agrário de Vairão Vairão 4485-661 Portugal IBE Institute of Evolutionary Biology (CSIC-UPF) Department of Experimental and Health Sciences Pompeu Fabra University Doctor Aiguader 88 Barcelona 08003 Spain Department of Animal and Plant Sciences University of Sheffield Sheffield United Kingdom Department of Biochemistry and Molecular Genetics University of Virginia Charlottesville 22908 VA United States TFome Research Group Bioinformatics Group Interdisciplinary Center of Bioinformatics Department of Computer Science University of Leipzig Härtelstrasse 16-18 Leipzig 04107 Germany Paul-Flechsig-Institute for Brain Research University of Leipzig Jahnallee 59 Leipzig 04109 Germany Faculty for Biology Chemistry and Pharmacy Freie Universität Berlin Königin-Luise-Straße 1-3 Berlin 14195 Germany Edinburgh Genomics University of Edinburgh Ashworth Laboratories King's Buildings Charlotte Auerbach Road Edinburgh EH9 3FL United Kingdom Museo Nacional de Ciencias Naturales Spanish Research Council (CSIC) José Gutiérrez Abascal 2 Madrid 28006 Spain German Centre for Integrative Biodiversity Research (IDiv) Halle-Jena-Leipzig Deutscher Platz 5e Leipzig 04103 Germany Grupo Rnomica Teórica y Computacional Departamento de Biologia Universidad Nacional de Colombia Bogota Colombia EcSeq Bioinformatics GmbH Sternwartenstraße 29 Leipzig 04103 Germany Computational Biology Department of Target Sciences GlaxoSmithKline Gunnels Wood Road Stevenage SG1 2NY United Kingdom Computational EvoDevo Group Department of Computer Science University of Leipzig Härtelstrasse 16-18 Leipzig 04107 Germany Bioinformatics Group Department of Computer Science University of Leipzig Härtelstrasse 16-18 Leipzig 04107 Germany Visual Data Analysis Lab ESAT/STADIUS KU Leuven Kasteelpark Arenberg 10 Leuven 3001 Belgium Imec KU Leuven Leuven Belgiu

Research in evolutionary biology has been progressively influenced by big data such as massive genome and transcriptome sequencing data, scalar measurements of several phenotypes on tens to thousands of individuals, as well as from collecting worldwide environmental data at an increasingly detailed scale. The handling and analysis of such data require computational skills that usually exceed the abilities of most traditionally trained evolutionary biologists. Here we discuss the advantages, challenges and considerations for organizing and running bioinformatics training courses of 2-3 weeks in length to introduce evolutionary biologists to the computational analysis of big data. Extended courses have the advantage of offering trainees the opportunity to learn a more comprehensive set of complementary topics and skills and allowing for more time to practice newly acquired competences. Many organizational aspects are common to any course, as the need to define precise learning objectives and the selection of appropriate and highly motivated instructors and trainees, among others. However, other features assume particular importance in extended bioinformatics training courses. To successfully implement a learning-by-doing philosophy, sufficient and enthusiastic teaching assistants (TAs) are necessary to offer prompt help to trainees. Further, a good balance between theoretical background and practice time needs to be provided and assured that the schedule includes enough flexibility for extra review sessions or further discussions if desired. A final project enables trainees to apply their newly learned skills to real data or case studies of their interest. To promote a friendly atmosphere throughout the course and to build a close-knit community after the course, allow time for some scientific discussions and social activities. In addition, to not exhaust trainees and TAs, some leisure time needs to be organized. Finally, all organization should be done while keeping

关键词： Active learning Bioinformatics Evolutionary biology Extended course Genomics High-throughput-sequencing Programming Sustainable course

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Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits (vol 50, pg 1412, 2018)

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NATURE GENETICS 2018年第12期50卷 1755-1755页

作者： Evangelou, Evangelos Warren, Helen R. Mosen-Ansorena, David Mifsud, Borbala Pazoki, Raha Gao, He Ntritsos, Georgios Dimou, Niki Cabrera, Claudia P. Karaman, Ibrahim Fu Liang Ng Evangelou, Marina Witkowska, Katarzyna Tzanis, Evan Hellwege, Jacklyn N. Giri, Ayush Edwards, Digna R. Velez Sun, Yan V. Cho, Kelly Gaziano, J. Michael Wilson, Peter W. F. Tsao, Philip S. Kovesdy, Csaba P. Esko, Tonu Magi, Reedik Milani, Lili Almgren, Peter Boutin, Thibaud Debette, Stephanie Ding, Jun Giulianini, Franco Holliday, Elizabeth G. Jackson, Anne U. Li-Gao, Ruifang Lin, Wei-Yu Luan, Jian'an Mangino, Massimo Oldmeadow, Christopher Prins, Bram Peter Qian, Yong Sargurupremraj, Muralidharan Shah, Nabi Surendran, Praveen Theriault, Sebastien Verweij, Niek Willems, Sara M. Zhao, Jing-Hua Amouyel, Philippe Connell, John de Mutsert, Renee Doney, Alex S. F. Farrall, Martin Menni, Cristina Morris, Andrew D. Noordam, Raymond Pare, Guillaume Poulter, Neil R. Shields, Denis C. Stanton, Alice Thom, Simon Abecasis, Goncalo Amin, Najaf Arking, Dan E. Ayers, Kristin L. Barbieri, Caterina M. Batini, Chiara Bis, Joshua C. Blake, Tineka Bochud, Murielle Boehnke, Michael Boerwinkle, Eric Boomsma, Dorret I. Bottinger, Erwin P. Braund, Peter S. Brumat, Marco Campbell, Archie Campbell, Harry Chakravarti, Aravinda Chambers, John C. Chauhan, Ganesh Ciullo, Marina Cocca, Massimiliano Collins, Francis Cordell, Heather J. Davies, Gail de Borst, Martin H. de Geus, Eco J. Deary, Ian J. Deelen, Joris Del Greco, Fabiola M. Demirkale, Cumhur Yusuf Dorr, Marcus Ehret, Georg B. Elosua, Roberto Enroth, Stefan Erzurumluoglu, A. Mesut Ferreira, Teresa Franberg, Mattias Franco, Oscar H. Gandin, Ilaria Gasparini, Paolo Giedraitis, Vilmantas Gieger, Christian Girotto, Giorgia Goel, Anuj Gow, Alan J. Gudnason, Vilmundur Guo, Xiuqing Gyllensten, Ulf Hamsten, Anders Harris, Tamara B. Harris, Sarah E. Hartman, Catharina A. Havulinna, Aki S. Hicks, Andrew A. Hofer, Edith Hofman, Albert Hottenga, Jouke-Jan Huffman, Jennifer E. Hwang, Shih-Jen Ingelsson, Erik James, Alan Jansen Department of Epidemiology and Biostatistics Imperial College London London UK Department of Hygiene and Epidemiology University of Ioannina Medical School Ioannina Greece William Harvey Research Institute Barts and The London School of Medicine and Dentistry Queen Mary University of London London UK National Institute for Health Research Barts Cardiovascular Biomedical Research Center Queen Mary University of London London UK MRC-PHE Centre for Environment and Health Imperial College London London UK Department of Mathematics Imperial College London London UK Division of Epidemiology Department of Medicine Institute for Medicine and Public Health Vanderbilt Genetics Institute Vanderbilt University Medical Center Tennessee Valley Healthcare System (626)/Vanderbilt University Nashville TN USA Vanderbilt Genetics Institute Vanderbilt Epidemiology Center Department of Obstetrics and Gynecology Vanderbilt University Medical Center Tennessee Valley Health Systems VA Nashville TN USA Department of Epidemiology Emory University Rollins School of Public Health Atlanta GA USA Department of Biomedical Informatics Emory University School of Medicine Atlanta GA USA Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC) VA Boston Healthcare System Boston MA USA Division of Aging Department of Medicine Brigham and Women’s Hospital Department of Medicine Harvard Medical School Boston MA USA Atlanta VAMC and Emory Clinical Cardiovascular Research Institute Atlanta GA USA VA Palo Alto Health Care System Division of Cardiovascular Medicine Stanford University School of Medicine Stanford CA USA Nephrology Section Memphis VA Medical Center and University of Tennessee Health Science Center Memphis TN USA Estonian Genome Center University of Tartu Tartu Estonia Program in Medical and Population Genetics Broad Institute of Harvard and MIT Cambridge MA USA Department Clinical Sciences Malmö Lund University Malmö Sweden MRC Human Genetics Un

High blood pressure is a highly heritable and modifiable risk factor for cardiovascular disease. We report the largest genetic association study of blood pressure traits (systolic, diastolic and pulse pressure) to date in over 1 million people of European ancestry. We identify 535 novel blood pressure loci that not only offer new biological insights into blood pressure regulation but also highlight shared genetic architecture between blood pressure and lifestyle exposures. Our findings identify new biological pathways for blood pressure regulation with potential for improved cardiovascular disease prevention in the future.

关键词： Cardiovascular diseases Genome informatics Genome-wide association studies

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Updated measurement of decay-time-dependent CP asymmetries in D0→K+K− and D0→π+π− decays

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Physical Review D 2020年第1期101卷 012005-012005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 P. Albicocco J. Albrecht F. Alessio M. Alexander A. Alfonso Albero G. Alkhazov P. Alvarez Cartelle A. A. Alves, Jr. S. Amato Y. Amhis L. An L. Anderlini G. Andreassi M. Andreotti F. Archilli P. d’Argent J. Arnau Romeu A. Artamonov M. Artuso K. Arzymatov E. Aslanides M. Atzeni B. Audurier S. Bachmann J. J. Back S. Baker V. Balagura W. Baldini A. Baranov R. J. Barlow S. Barsuk W. Barter M. Bartolini F. Baryshnikov G. Bassi V. Batozskaya B. Batsukh A. Battig V. Battista A. Bay M. Becker F. Bedeschi I. Bediaga A. Beiter L. J. Bel V. Belavin S. Belin N. Beliy V. Bellee K. Belous I. Belyaev E. Ben-Haim G. Bencivenni S. Benson S. Beranek A. Berezhnoy R. Bernet D. Berninghoff H. C. Bernstein E. Bertholet A. Bertolin C. Betancourt F. Betti M. O. Bettler M. van Beuzekom Ia. Bezshyiko S. Bhasin J. Bhom M. S. Bieker S. Bifani P. Billoir A. Bizzeti M. Bjørn M. P. Blago T. Blake F. Blanc S. Blusk D. Bobulska V. Bocci O. Boente Garcia T. Boettcher A. Boldyrev A. Bondar N. Bondar S. Borghi M. Borisyak M. Borsato J. T. Borsuk T. J. V. Bowcock C. Bozzi S. Braun A. Brea Rodriguez M. Brodski J. Brodzicka A. Brossa Gonzalo D. Brundu E. Buchanan A. Buonaura C. Burr A. Bursche J. S. Butter J. Buytaert W. Byczynski S. Cadeddu H. Cai R. Calabrese L. Calero Diaz S. Cali R. Calladine M. Calvi M. Calvo Gomez A. Camboni P. Campana D. H. Campora Perez L. Capriotti A. Carbone G. Carboni R. Cardinale A. Cardini P. Carniti K. Carvalho Akiba A. Casais Vidal G. Casse M. Cattaneo G. Cavallero R. Cenci J. Cerasoli M. G. Chapman M. Charles Ph. Charpentier G. Chatzikonstantinidis M. Chefdeville V. Chekalina C. Chen S. Chen A. Chernov S.-G. Chitic V. Chobanova M. Chrzaszcz A. Chubykin P. Ciambrone M. F. Cicala X. Cid Vidal G. Ciezarek F. Cindolo P. E. L. Clarke M. Clemencic H. V. Cliff J. Closier J. L. Cobbledick V. Coco J. A. B. Coelho J. Cogan E. Cogneras L. Cojocariu P. Collins T. Colombo A. Comerma-Montells A. Contu N. Cooke G. Coombs 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 INFN Laboratori Nazionali di Frascati Frascati Italy 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 Petersburg Nuclear Physics Institute NRC Kurchatov Institute (PNPI NRC KI) Gatchina Russia Imperial College London London United Kingdom Universidade Federal do Rio de Janeiro (UFRJ) Rio de Janeiro Brazil LAL Université Paris-Sud CNRS/IN2P3 Université Paris-Saclay Orsay France INFN Sezione di Firenze Firenze Italy Institute of Physics Ecole Polytechnique Fédérale de Lausanne (EPFL) Lausanne Switzerland INFN Sezione di Ferrara Ferrara Italy Physikalisches Institut Ruprecht-Karls-Universität Heidelberg Heidelberg Germany Aix Marseille Université CNRS/IN2P3 CPPM Marseille France Institute for High Energy Physics NRC Kurchatov Institute (IHEP NRC KI) Protvino Russia Syracuse University Syracuse New York USA Yandex School of Data Analysis Moscow Russia INFN Sezione di Cagliari Monserrato Italy Department of Physics University of Warwick Coventry United Kingdom Department of Physics and Astronomy University of Manchester Manchester United Kingdom INFN Sezione di Genova Genova Italy INFN Sezione

A search for decay-time-dependent charge-parity (CP) asymmetry in D0→K+K− and D0→π+π− decays is performed at the LHCb experiment using proton-proton collision data recorded at a center-of-mass energy of 13 TeV, and corresponding to an integrated luminosity of 5.4 fb−1. The D0 mesons are required to originate from semileptonic decays of b hadrons, such that the charge of the muon identifies the flavor of the neutral D meson at production. The asymmetries in the effective decay widths of D0 and D¯0 mesons are determined to be AΓ(K+K−)=(−4.3±3.6±0.5)×10−4 and AΓ(π+π−)=(2.2±7.0±0.8)×10−4, where the uncertainties are statistical and systematic, respectively. The results are consistent with CP symmetry and, when combined with previous LHCb results, yield AΓ(K+K−)=(−4.4±2.3±0.6)×10−4 and AΓ(π+π−)=(2.5±4.3±0.7)×10−4.

关键词： Particle decays Particle interactions

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Preface

Communications in Computer and Information Science

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Communications in computer and Information science 2018年 934卷 V-VI页

作者： Kuznetsov, Sergei O. Osipov, Gennady S. Stefanuk, Vadim L. Department of Data Analysis and Artificial Intelligence National Research University Higher School of Economics Moscow Russia Federal Research Center Computer Science and Control Institute of Informatics Problems Moscow Russia Institute for Information Transmission Problems Russian Academy of Sciences Moscow Russia

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Prompt Λ _c ⁺ production in pPb collisions at √sNN=5.02 TeV

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Journal of High Energy Physics 2019年第2期2019卷 1页

作者： Aaij, R. Adeva, B. Adinolfi, M. Aidala, C.A. Ajaltouni, Z. Akar, S. Albicocco, P. Albrecht, J. Alessio, F. Alexander, M. Alfonso Albero, A. Ali, S. Alkhazov, G. Alvarez Cartelle, P. Alves, A.A. Amato, S. Amerio, S. Amhis, Y. An, L. Anderlini, L. Andreassi, G. Andreotti, M. Andrews, J.E. Appleby, R.B. Archilli, F. d’Argent, P. Arnau Romeu, J. Artamonov, A. Artuso, M. Arzymatov, K. Aslanides, E. Atzeni, M. Audurier, B. Bachmann, S. Back, J.J. Baker, S. Balagura, V. Baldini, W. Baranov, A. Barlow, R.J. Barsuk, S. Barter, W. Baryshnikov, F. Batozskaya, V. Batsukh, B. Battista, V. Bay, A. Beddow, J. Bedeschi, F. Bediaga, I. Beiter, A. Bel, L.J. Beliy, N. Bellee, V. Belloli, N. Belous, K. Belyaev, I. Ben-Haim, E. Bencivenni, G. Benson, S. Beranek, S. Berezhnoy, A. Bernet, R. Berninghoff, D. Bertholet, E. Bertolin, A. Betancourt, C. Betti, F. Bettler, M.O. van Beuzekom, M. Bezshyiko, Ia. Bhasin, S. Bhom, J. Bifani, S. Billoir, P. Birnkraut, A. Bizzeti, A. Bjørn, M. Blago, M.P. Blake, T. Blanc, F. Blusk, S. Bobulska, D. Bocci, V. Boente Garcia, O. Boettcher, T. Bondar, A. Bondar, N. Borghi, S. Borisyak, M. Borsato, M. Bossu, F. Boubdir, M. Bowcock, T.J.V. Bozzi, C. Braun, S. Brodski, M. Brodzicka, J. Brossa Gonzalo, A. Brundu, D. Buchanan, E. Buonaura, A. Burr, C. Bursche, A. Buytaert, J. Byczynski, W. Cadeddu, S. Cai, H. Calabrese, R. Calladine, R. Calvi, M. Calvo Gomez, M. Camboni, A. Campana, P. Campora Perez, D.H. Capriotti, L. Carbone, A. Carboni, G. Cardinale, R. Cardini, A. Carniti, P. Carson, L. Carvalho Akiba, K. Casse, G. Cassina, L. Cattaneo, M. Cavallero, G. Cenci, R. Chamont, D. Chapman, M.G. Charles, M. Charpentier, Ph. Chatzikonstantinidis, G. Chefdeville, M. Chekalina, V. Chen, C. Chen, S. Chitic, S.-G. Chobanova, V. Chrzaszcz, M. Chubykin, A. Ciambrone, P. Cid Vidal, X. Ciezarek, G. Clarke, P.E.L. Clemencic, M. Cliff, H.V. Closier, J. Coco, V. Coelho, J.A.B. Cogan, J. Cogneras, E. Cojocariu, L. Collins, P. Colombo, T. Comerma-Montells, A. Contu, A. Coombs, G. Coquereau, S. Corti, G. Corvo, M. Costa Sobra Centro Brasileiro de Pesquisas Físicas (CBPF) Rio de Janeiro Brazil Universidade Federal do Rio de Janeiro (UFRJ) Rio de Janeiro Brazil Center for High Energy Physics Tsinghua University Beijing China Univ. Grenoble Alpes Univ. Savoie Mont Blanc CNRS IN2P3-LAPP Annecy France Clermont Université Université Blaise Pascal CNRS/IN2P3 LPC Clermont-Ferrand France Aix Marseille Univ CNRS/IN2P3 CPPM Marseille France LAL Univ. Paris-Sud CNRS/IN2P3 Université Paris-Saclay Orsay France LPNHE Sorbonne Université Paris Diderot Sorbonne Paris Cité CNRS/IN2P3 Paris France I. Physikalisches Institut RWTH Aachen University Aachen Germany Fakultät Physik Technische Universität Dortmund Dortmund Germany Max-Planck-Institut für Kernphysik (MPIK) Heidelberg Germany Physikalisches Institut Ruprecht-Karls-Universität Heidelberg Heidelberg Germany School of Physics University College Dublin Dublin Ireland INFN Sezione di Bari Bari Italy INFN Sezione di Bologna Bologna Italy INFN Sezione di Ferrara Ferrara Italy INFN Sezione di Firenze Firenze Italy INFN Laboratori Nazionali di Frascati Frascati Italy INFN Sezione di Genova Genova Italy INFN Sezione di Milano-Bicocca Milano Italy INFN Sezione di Milano Milano Italy INFN Sezione di Cagliari Monserrato Italy INFN Sezione di Padova Padova Italy INFN Sezione di Pisa Pisa Italy INFN Sezione di Roma Tor Vergata Roma Italy INFN Sezione di Roma La Sapienza Roma Italy Nikhef National Institute for Subatomic Physics Amsterdam Netherlands Nikhef National Institute for Subatomic Physics and VU University Amsterdam Amsterdam Netherlands Henryk Niewodniczanski Institute of Nuclear Physics Polish Academy of Sciences Kraków Poland AGH - University of Science and Technology Faculty of Physics and Applied Computer Science Kraków Poland National Center for Nuclear Research (NCBJ) Warsaw Poland Horia Hulubei National Institute of Physics and Nuclear Engineering Bucharest-Magurele Romania Petersburg Nuclear Physics Institute

The prompt production of Λ c + baryons is studied in proton-lead collisions collected with the LHCb detector at the LHC. The data sample corresponds to an integrated luminosity of 1.58 nb −1 recorded at a nucleon-nuc... 详细信息

The prompt production of Λ _c ⁺ baryons is studied in proton-lead collisions collected with the LHCb detector at the LHC. The data sample corresponds to an integrated luminosity of 1.58 nb ⁻¹ recorded at a nucleon-nucleon centre-of-mass energy of sNN=5.02 TeV. Measurements of the differential cross-section and the forwardbackward production ratio are reported for Λ _c ⁺ baryons with transverse momenta in the range 2 < p _T < 10 GeV/c and rapidities in the ranges 1.5 < y ^∗ < 4.0 and −4.5 < y ^∗ < −2.5 in the nucleon-nucleon centre-of-mass system. The ratio of cross-sections of Λ _c ⁺ baryons and D ⁰ mesons is also reported. The results are compared with next-to-leading order calculations that use nuclear parton distribution functions.[Figure not available: see fulltext.] © 2019, The Author(s).

关键词： Charm physics Forward physics Heavy Ion Experiments Heavy quark production

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