4.3 Article

Identification of heavy-flavour jets with the CMS detector in pp collisions at 13 TeV

期刊

JOURNAL OF INSTRUMENTATION
卷 13, 期 -, 页码 -

出版社

IOP Publishing Ltd
DOI: 10.1088/1748-0221/13/05/P05011

关键词

Particle identification methods; Pattern recognition, cluster finding, calibration and fitting methods; Performance of High Energy Physics Detectors

资金

  1. Austrian Federal Ministry of Science, Research and Economy
  2. Austrian Science Fund
  3. Belgian Fonds de la Recherche Scientifique
  4. Fonds voor Wetenschappelijk Onderzoek
  5. CNPq
  6. CAPES
  7. FAPERJ
  8. FAPESP
  9. Bulgarian Ministry of Education and Science
  10. CERN
  11. Chinese Academy of Sciences
  12. National Natural Science Foundation of China
  13. Colombian Funding Agency (COLCIENCIAS)
  14. Croatian Ministry of Science, Education and Sport
  15. Croatian Science Foundation
  16. Research Promotion Foundation, Cyprus
  17. Secretariat for Higher Education, Science, Technology and Innovation, Ecuador
  18. Ministry of Education and Research, Estonia
  19. Estonian Research Council, Estonia [IUT23-4, IUT23-6]
  20. European Regional Development Fund, Estonia
  21. Academy of Finland, Finnish Ministry of Education and Culture
  22. Helsinki Institute of Physics
  23. Institut National de Physique Nucleaire et de Physique des Particules / CNRS, France
  24. Commissariat a l'Energie Atomique et aux Energies Alternatives / CEA, France
  25. Bundesministerium fur Bildung und Forschung, Germany
  26. Deutsche Forschungsgemeinschaft, Germany
  27. Helmholtz-Gemeinschaft Deutscher Forschungszentren, Germany
  28. General Secretariat for Research and Technology, Greece
  29. National Scientific Research Foundation, Hungary
  30. National Innovation Office, Hungary
  31. Department of Atomic Energy, India
  32. Department of Science and Technology, India
  33. Institute for Studies in Theoretical Physics and Mathematics, Iran
  34. Science Foundation, Ireland
  35. Istituto Nazionale di Fisica Nucleare, Italy
  36. Ministry of Science, ICT and Future Planning, Republic of Korea
  37. National Research Foundation (NRF), Republic of Korea
  38. Lithuanian Academy of Sciences
  39. Ministry of Education (Malaysia)
  40. University of Malaya (Malaysia)
  41. BUAP
  42. CINVESTAV
  43. CONACYT
  44. LNS
  45. SEP
  46. UASLP-FAI
  47. Ministry of Business, Innovation and Employment, New Zealand
  48. Pakistan Atomic Energy Commission
  49. Ministry of Science and Higher Education, Poland
  50. National Science Centre, Poland
  51. Fundacao para a Ciencia e a Tecnologia, Portugal
  52. JINR, Dubna
  53. Ministry of Education and Science of the Russian Federation
  54. Federal Agency of Atomic Energy of the Russian Federation
  55. Russian Academy of Sciences
  56. Russian Foundation for Basic Research
  57. Russian Competitiveness Program of NRNU MEPhI
  58. Ministry of Education, Science and Technological Development of Serbia
  59. Secretaria de Estado de Investigacion, Desarrollo e Innovacion, Programa Consolider-Ingenio, Plan de Ciencia, Tecnologia e Innovacion del Principado de Asturias, Spain [20132017]
  60. Fondo Europeo de Desarrollo Regional, Spain
  61. ETH Board
  62. ETH Zurich
  63. PSI
  64. SNF
  65. UniZH
  66. Canton Zurich
  67. SER
  68. Ministry of Science and Technology, Taipei
  69. Thailand Center of Excellence in Physics
  70. Institute for the Promotion of Teaching Science and Technology of Thailand
  71. Special Task Force for Activating Research
  72. National Science and Technology Development Agency of Thailand
  73. Scientific and Technical Research Council of Turkey
  74. Turkish Atomic Energy Authority
  75. National Academy of Sciences of Ukraine
  76. State Fund for Fundamental Researches, Ukraine
  77. Science and Technology Facilities Council, UK
  78. US Department of Energy
  79. US National Science Foundation
  80. Marie-Curie programme
  81. European Research Council
  82. European Union [675440]
  83. Leventis Foundation
  84. A. P. Sloan Foundation
  85. Alexander von Humboldt Foundation
  86. Belgian Federal Science Policy Office
  87. Fonds pour la Formation a la Recherche dans l'Industrie et dans l'Agriculture (FRIA-Belgium)
  88. Agentschap voor Innovatie door Wetenschap en Technologie (IWT-Belgium)
  89. Ministry of Education, Youth and Sports (MEYS) of the Czech Republic
  90. Council of Scientific and Industrial Research, India
  91. HOMING PLUS programme of the Foundation for Polish Science
  92. European Union, Regional Development Fund
  93. Ministry of Science and Higher Education
  94. National Science Center (Poland) [Harmonia 2014/14/M/ST2/00428, Opus 2014/13/B/ST2/02543, 2014/15/B/ST2/03998, 2015/19/B/ST2/02861, Sonata-bis 2012/07/E/ST2/01406]
  95. Qatar National Research Fund
  96. Programa Severo Ochoa del Principado de Asturias
  97. EU-ESF
  98. Greek NSRF
  99. Rachadapisek Sompot Fund for Postdoctoral Fellowship
  100. Chulalongkorn University
  101. Chulalongkorn Academic into Its 2nd Century Project Advancement Project (Thailand)
  102. Welch Foundation [C-1845]
  103. Weston Havens Foundation (USA)
  104. Ministry of Science and Technology
  105. STFC [ST/N000242/1] Funding Source: UKRI
  106. Direct For Mathematical & Physical Scien [1508869, 1606321] Funding Source: National Science Foundation
  107. Division Of Physics [1607262, 1151640] Funding Source: National Science Foundation

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Many measurements and searches for physics beyond the standard model at the LHC rely on the efficient identification of heavy-flavour jets, i.e. jets originating from bottom or charm quarks. In this paper, the discriminating variables and the algorithms used for heavy-flavour jet identification during the first years of operation of the CMS experiment in proton-proton collisions at a centre-of-mass energy of 13 TeV, are presented. Heavy-flavour jet identification algorithms have been improved compared to those used previously at centre-of-mass energies of 7 and 8 TeV. For jets with transverse momenta in the range expected in simulated t (t) over bar events, these new developments result in an efficiency of 68% for the correct identification of a b jet for a probability of 1% of misidentifying a light-flavour jet. The improvement in relative efficiency at this misidentification probability is about 15%, compared to previous CMS algorithms. In addition, for the first time algorithms have been developed to identify jets containing two b hadrons in Lorentz-boosted event topologies, as well as to tag c jets. The large data sample recorded in 2016 at a centre-of-mass energy of 13 TeV has also allowed the development of new methods to measure the efficiency and misidentification probability of heavy-flavour jet identification algorithms. The b jet identification efficiency is measured with a precision of a few per cent at moderate jet transverse momenta (between 30 and 300 GeV) and about 5% at the highest jet transverse momenta (between 500 and 1000 GeV).

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