4.3 Article

Identification of b-quark jets with the CMS experiment

Journal

JOURNAL OF INSTRUMENTATION
Volume 8, Issue -, Pages -

Publisher

IOP Publishing Ltd
DOI: 10.1088/1748-0221/8/04/P04013

Keywords

Large detector-systems performance; Pattern recognition, cluster finding, calibration and fitting methods; Performance of High Energy Physics Detectors

Funding

  1. Austrian Federal Ministry of Science and Research
  2. Belgium Fonds de la Recherche Scientifique
  3. Fonds voor Wetenschappelijk Onderzoek
  4. CNPq
  5. CAPES
  6. FAPERJ
  7. FAPESP
  8. Bulgarian Ministry of Education and Science
  9. CERN
  10. Chinese Academy of Sciences
  11. Ministry of Science and Technology
  12. National Natural Science Foundation of China
  13. Colombian Funding Agency (COLCIENCIAS)
  14. Croatian Ministry of Science, Education and Sport
  15. Research Promotion Foundation, Cyprus
  16. Ministry of Education and Research [SF0690030s09]
  17. European Regional Development Fund, Estonia
  18. Academy of Finland
  19. Finnish Ministry of Education and Culture
  20. Helsinki Institute of Physics
  21. Institut National de Physique Nucleaire et de Physique des Particules / CNRS, France
  22. Commissariat a l' Energie Atomique et aux Energies Alternatives / CEA, France
  23. Bundesministerium fur Bildung und Forschung, Germany
  24. Deutsche Forschungsgemeinschaft, Germany
  25. Helmholtz-Gemeinschaft Deutscher Forschungszentren, Germany
  26. General Secretariat for Research and Technology, Greece
  27. National Scientific Research Foundation
  28. National Office for Research and Technology, Hungary
  29. Department of Atomic Energy and the Department of Science and Technology, India
  30. Institute for Studies in Theoretical Physics and Mathematics, Iran
  31. Science Foundation, Ireland
  32. Istituto Nazionale di Fisica Nucleare, Italy
  33. Korean Ministry of Education, Science and Technology, India
  34. World Class University program of NRF, Korea
  35. Lithuanian Academy of Sciences
  36. CINVESTAV
  37. CONACYT
  38. SEP
  39. UASLP-FAI
  40. Ministry of Science and Innovation, New Zealand
  41. Pakistan Atomic Energy Commission
  42. Ministry of Science and Higher Education
  43. National Science Centre, Poland
  44. Fundacao para a Ciencia e a Tecnologia, Portugal
  45. JINR (Armenia)
  46. JINR (Belarus)
  47. JINR (Georgia)
  48. JINR (Ukraine)
  49. JINR (Uzbekistan)
  50. Ministry of Education and Science of the Russian Federation
  51. Federal Agency of Atomic Energy of the Russian Federation
  52. Russian Academy of Sciences
  53. Russian Foundation for Basic Research
  54. Ministry of Science and Technological Development of Serbia
  55. Secretaria de Estado de Investigacion, Desarrollo e Innovacion, Spain
  56. Programa Consolider-Ingenio, Spain
  57. ETH Board
  58. ETH Zurich
  59. PSI
  60. SNF
  61. UniZH
  62. Canton Zurich
  63. SER
  64. National Science Council, Taipei
  65. Scientific and Technical Research Council of Turkey
  66. Turkish Atomic Energy Authority
  67. Science and Technology Facilities Council, UK
  68. US Department of Energy
  69. US National Science Foundation
  70. Marie-Curie programme
  71. European Research Council (European Union)
  72. Leventis Foundation
  73. A. P. Sloan Foundation
  74. Alexander von Humboldt Foundation
  75. Austrian Science Fund (FWF)
  76. Belgian Federal Science Policy Office
  77. Fonds pour la Formation a la Recherche dans l'Industrie et dans l'Agriculture (FRIA-Belgium)
  78. Agentschap voor Innovatie door Wetenschap en Technologie (IWT-Belgium)
  79. Council of Science and Industrial Research, India
  80. Compagnia di San Paolo (Torino)
  81. Foundation for Polish Science
  82. European Union
  83. STFC [ST/K003844/1, ST/I505572/1, ST/J004901/1, ST/H00081X/2, ST/K001604/1, ST/L00609X/1, ST/I005912/1, ST/J005665/1, ST/F007094/1] Funding Source: UKRI
  84. Science and Technology Facilities Council [ST/L00609X/1 GRIDPP, ST/K001604/1 CMS Upgrade, ST/K001604/1 SuperNEMO, ST/J005665/1, ST/K001604/1 LHCb, ST/L00609X/1, ST/I505572/1, ST/J004901/1, ST/K003844/1, ST/I005912/1 GRIDPP, CMS, ST/K001604/1 DMUK, ST/K001604/1 LHCb Upgrades, ST/K001604/1 GRIDPP, ST/K001604/1 MICE/UKNF, ST/K003844/1 GRIDPP, GRIDPP, ST/I005912/1, ST/I003622/1 GRIDPP, ST/F007094/1, ST/K001604/1, ST/K001604/1 T2K] Funding Source: researchfish
  85. Direct For Mathematical & Physical Scien
  86. Division Of Physics [0969704, 1211067, 0969555] Funding Source: National Science Foundation
  87. Direct For Mathematical & Physical Scien
  88. Division Of Physics [1205960, 1151640] Funding Source: National Science Foundation

Ask authors/readers for more resources

At the Large Hadron Collider, the identification of jets originating from b quarks is important for searches for new physics and for measurements of standard model processes. A variety of algorithms has been developed by CMS to select b-quark jets based on variables such as the impact parameters of charged-particle tracks, the properties of reconstructed decay vertices, and the presence or absence of a lepton, or combinations thereof. The performance of these algorithms has been measured using data from proton-proton collisions at the LHC and compared with expectations based on simulation. The data used in this study were recorded in 2011 at root s = 7TeV for a total integrated luminosity of 5.0 fb(-1). The efficiency for tagging b-quark jets has been measured in events from multijet and t-quark pair production. CMS has achieved a b-jet tagging efficiency of 85% for a light-parton misidentification probability of 10% in multijet events. For analyses requiring higher purity, a misidentification probability of only 1.5% has been achieved, for a 70% b-jet tagging efficiency.

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