Jet Physics at the LHC pp 61-110

Part of the Springer Tracts in Modern Physics book series (STMP, volume 268) | Cite as

Jet Measurement



This chapter introduces the necessary experimental concepts and tools needed for a generic jet analysis at the LHC. The sections are ordered in a similar way as they would typically appear in an experimental publication and start with a synopsis of the measuring apparatus.


  1. 1.
    E. Evans, Lyndon, E. Bryant, Philip, LHC machine. JINST 3, S08001 (2008). doi:10.1088/1748-0221/3/08/S08001
  2. 2.
    R.M. Barnett et al., Physics at the Terascale, 1st edn. (Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim, Germany, 2011)Google Scholar
  3. 3.
    R. Alemany-Fernandez et al., The Large Hadron Collider: Harvest of Run 1, 1st edn. (Springer, Berlin, 2015)Google Scholar
  4. 4.
    ATLAS Collaboration, The ATLAS experiment at the CERN large hadron collider. JINST 3, S08003 (2008). doi:10.1088/1748-0221/3/08/S08003
  5. 5.
    CMS Collaboration, The CMS experiment at the CERN LHC. JINST 3, S08004 (2008). doi:10.1088/1748-0221/3/08/S08004
  6. 6.
    ALICE Collaboration, The ALICE experiment at the CERN LHC. JINST 3, S08002 (2008). doi:10.1088/1748-0221/3/08/S08002
  7. 7.
    LHCb Collaboration, The LHCb detector at the LHC. JINST 3, S08005 (2008). doi:10.1088/1748-0221/3/08/S08005
  8. 8.
    ATLAS Collaboration, Jet energy measurement and its systematic uncertainty in proton-proton collisions at \(\sqrt{s}=7\) TeV with the ATLAS detector. Eur. Phys. J. C. 75, 17 (2015). doi:10.1140/epjc/s10052-014-3190-y, arXiv:1406.0076
  9. 9.
    CMS Collaboration, Jet energy scale and resolution in the CMS experiment in pp collisions at 8 TeV. CMS-PAPER-JME-13-004 (2016). Submitted to JINSTGoogle Scholar
  10. 10.
    M. Cacciari, G.P. Salam, G. Soyez, The anti-\(k_t\) jet clustering algorithm. JHEP 04, 063 (2008). doi:10.1088/1126-6708/2008/04/063, arXiv:0802.1189
  11. 11.
    W. Lampl et al., Calorimeter clustering algorithms: description and performance. Technical report, ATL-LARG-PUB-2008-002 (2008)Google Scholar
  12. 12.
    CMS Collaboration, Particle-flow event reconstruction in CMS and performance for Jets, Taus, and MET. Technical report, CMS-PAS-PFT-09-001, CERN (2009)Google Scholar
  13. 13.
    CMS Collaboration, Commissioning of the particle-flow event reconstruction with the first LHC collisions recorded in the CMS detector. Technical report, CMS-PAS-PFT-10-001, CERN (2010)Google Scholar
  14. 14.
    C. Buttar et al., Standard model handles and candles working group: tools and jets summary report, in Proceedings, 5th Les Houches Workshop 2007 on Physics at TeV colliders (Les Houches 2007) (Les Houches, France, June 11–29, 2007), p. 121, arXiv:0803.0678
  15. 15.
    A. Buckley et al., General-purpose event generators for LHC physics. Phys. Rept. 504, 145 (2011). doi:10.1016/j.physrep.2011.03.005, arXiv:1101.2599
  16. 16.
    ATLAS and CMS Collaboration, Jet energy scale uncertainty correlations between ATLAS and CMS. Technical report, ATL-PHYS-PUB-2014-020 CMS-PAS-JME-14-003, CERN (2014)Google Scholar
  17. 17.
    ATLAS and CMS Collaboration, Jet energy scale uncertainty correlations between ATLAS and CMS at 8 TeV. Technical report, ATL-PHYS-PUB-2015-049 CMS-PAS-JME-15-001, CERN (2015)Google Scholar
  18. 18.
    CMS Collaboration, Measurement of the inclusive jet cross section in pp collisions at \(\sqrt{s}=7\) TeV. Phys. Rev. Lett. 107, 132001 (2011). doi:10.1103/PhysRevLett.107.132001, arXiv:1106.0208
  19. 19.
    ATLAS Collaboration, Measurement of dijet cross sections in pp collisions at 7 TeV centre-of-mass energy using the ATLAS detector. JHEP 05, 059 (2014). doi:10.1007/JHEP05(2014)059, arXiv:1312.3524
  20. 20.
    CMS Collaboration, Measurements of differential jet cross sections in proton-proton collisions at \(\sqrt{s}=7\) TeV with the CMS detector. Phys. Rev. D 87, 112002 (2013). doi:10.1103/PhysRevD.87.112002, arXiv:1212.6660
  21. 21.
    C.J. Clopper, E.S. Pearson, The use of confidence or fiducial limits illustrated in the case of the binomial. Biometrika 26, 404 (1934). doi:10.1093/biomet/26.4.404 CrossRefMATHGoogle Scholar
  22. 22.
    E.B. Wilson, Probable Inference, the law of succession, and statistical inference. J. Am. Stat. Assoc. 22, 209 (1927). doi:10.1080/01621459.1927.10502953 CrossRefGoogle Scholar
  23. 23.
    V. Lendermann et al., Combining triggers in HEP data analysis. Nucl. Instrum. Meth. A 604, 707 (2009). doi:10.1016/j.nima.2009.03.173, arXiv:0901.4118
  24. 24.
    F. Stober, Measurement of the three-jet mass cross-section at \(\sqrt{s}=7\,\)TeV. PhD thesis, KIT (Karlsruher Institut für Technologie), October, 2012Google Scholar
  25. 25.
    S. Agostinelli et al., GEANT4: a simulation toolkit. Nucl. Instrum. Methods Phys. Res. A 506, 250 (2003). doi:10.1016/S0168-9002(03)01368-8 ADSCrossRefGoogle Scholar
  26. 26.
    D0 Collaboration, Jet energy scale determination in the D0 experiment. Nucl. Instrum. Meth. A 763, 442 (2014). doi:10.1016/j.nima.2014.05.044, arXiv:1312.6873
  27. 27.
    CMS Collaboration, Determination of jet energy calibration and transverse momentum resolution in CMS. JINST 6, P11002 (2011). doi:10.1088/1748-0221/6/11/P11002, arXiv:1107.4277
  28. 28.
    CMS Collaboration, Single-particle response in the CMS calorimeters. Technical report, CMS-PAS-JME-10-008 (2010)Google Scholar
  29. 29.
    A. Giammanco, The fast simulation of the CMS experiment, in Proceedings, 20th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2013), vol. 513 (Amsterdam, Netherlands, October 14–18, 2014), p. 022012. doi:10.1088/1742-6596/513/2/022012
  30. 30.
    ATLAS Collaboration, Jet energy measurement with the ATLAS detector in proton-proton collisions at \(\sqrt{s}=7\) TeV. Eur. Phys. J. C. 73, 2304 (2013). doi:10.1140/epjc/s10052-013-2304-2, arXiv:1112.6426
  31. 31.
    CMS Collaboration, Performance of CMS muon reconstruction in \(pp\) collision events at \(\sqrt{s}=7\) TeV. JINST 7, P10002 (2012). doi:10.1088/1748-0221/7/10/P10002, arXiv:1206.4071
  32. 32.
    CMS Collaboration, Energy calibration and resolution of the CMS electromagnetic calorimeter in pp collisions at \(\sqrt{s}\) = 7 TeV. JINST 8, P09009 (2013). doi:10.1088/1748-0221/8/09/P09009, arXiv:1306.2016
  33. 33.
    CMS Collaboration, Performance of photon reconstruction and identification with the CMS detector in proton-proton collisions at \(\sqrt{s} = 8\) TeV. JINST 10, P08010 (2015). doi:10.1088/1748-0221/10/08/P08010, arXiv:1502.02702
  34. 34.
    R.K. Ellis, W.J. Stirling, B.R. Webber, QCD and Collider Physics. Cambridge Monographs on Particle Physics, Nuclear Physics and Cosmology (Cambridge University Press, Cambridge, 1996)Google Scholar
  35. 35.
    A. Banfi, G.P. Salam, G. Zanderighi, Infrared safe definition of jet flavor. Eur. Phys. J. C 47, 113 (2006). doi:10.1140/epjc/s2006-02552-4, arXiv:hep-ph/0601139
  36. 36.
    L. Demortier, Equivalence of the best-fit and covariance matrix methods for comparing binned data with a model in the presence of correlated systematic uncertainties. CDF Note 8661 (1999)Google Scholar
  37. 37.
    D. Stump et al., Uncertainties of predictions from parton distribution functions. 1. The Lagrange multiplier method. Phys. Rev. D 65, 014012 (2001). doi:10.1103/PhysRevD.65.014012, arXiv:hep-ph/0101051
  38. 38.
    L. Lyons, A.J. Martin, D.H. Saxon, On the determination of the \(B\) lifetime by combining the results of different experiments. Phys. Rev. D 41, 982 (1990). doi:10.1103/PhysRevD.41.982 ADSCrossRefGoogle Scholar
  39. 39.
    G. D’Agostini, Bayesian Reasoning in Data Analysis: A Critical Introduction (World Scientific Publishing Co. Pte. Ltd., Singapore, 2003)Google Scholar
  40. 40.
    R.D. Ball et al., Fitting parton distribution data with multiplicative normalization uncertainties. JHEP 05, 075 (2010). doi:10.1007/JHEP05(2010) 075, arXiv:0912.2276
  41. 41.
    ATLAS Collaboration, Measurement of the inclusive jet cross-section in proton-proton collisions at \(\sqrt{s}=7\) TeV using 4.5 fb\(^{-1}\) of data with the ATLAS detector. JHEP 02, 153 (2015). doi:10.1007/JHEP02(2015)153, arXiv:1410.8857
  42. 42.
    M.J. Oreglia, A study of the reactions \(\psi ^\prime \rightarrow \gamma \gamma \psi \). PhD thesis, SLAC (Stanford Linear Accelerator Center), December, 1980Google Scholar
  43. 43.
    ATLAS Collaboration, Search for scalar diphoton resonances in the mass range \(65-600\) GeV with the ATLAS detector in \(pp\) collision data at \(\sqrt{s}=8\) TeV. Phys. Rev. Lett. 113, 171801 (2014). doi:10.1103/PhysRevLett.113.171801, arXiv:1407.6583
  44. 44.
    R. Barlow et al., Data Analysis in High Energy Physics, 1st edn. (Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim, Germany, 2013)Google Scholar
  45. 45.
    G. Bohm, G. Zech, Introduction to Statistics and Data Analysis for Physicists, 1st edn. (Deutsches Elektronen-Synchrotron, Hamburg, Germany, 2010)Google Scholar
  46. 46.
    G. Cowan, Statistical Data Analysis, 1st edn. (Clarendon Press, Oxford, 1998)Google Scholar
  47. 47.
    G. Zech, Comparing statistical data to Monte Carlo simulation: parameter fitting and unfolding. Technical report, DESY-95-113, (DESY, Hamburg, 1995)Google Scholar
  48. 48.
    G. Cowan, A survey of unfolding methods for particle physics, in Proceedings, Conference on Advanced Statistical Techniques in Particle Physics, vol. C0203181 (Durham, UK, March 18–22, 2002), p. 248Google Scholar
  49. 49.
    H.B. Prosper, L. Lyons (eds.), Proceedings, PHYSTAT 2011 Workshop on Statistical Issues Related to Discovery Claims in Search Experiments and Unfolding (CERN. CERN, Geneva, Switzerland, January 17–20, 2011). doi:10.5170/CERN-2011-006
  50. 50.
    CMS Collaboration, Measurement of dijet azimuthal decorrelations in pp collisions at \(\sqrt{s} = 8\) TeV’ CMS-PAPER-SMP-14-015 (2016). Accepted by Eur. Phys. J. C, arXiv:1602.04384
  51. 51.
    D.B.R.A.P. Dempster, N.M. Laird, Maximum likelihood from incomplete data via the EM algorithm. J. Royal Stat. Soc. Ser. B Methodol. 39, 1 (1977)Google Scholar
  52. 52.
    Y. Vardi, L.A. Shepp, L. Kaufman, A statistical model for positron emission tomography. J. Am. Stat. Assoc. 80, 8 (1985). doi:10.1080/01621459.1985.10477119 MathSciNetCrossRefMATHGoogle Scholar
  53. 53.
    A. Tikhonov, On the solution of improperly posed problems and the method of regularization. Soviet Math. Dokl. 5, 1035 (1963)MATHGoogle Scholar
  54. 54.
    D.L. Phillips, A technique for the numerical solution of certain integral equations of the first kind. J. ACM 9, 84 (1962). doi:10.1145/321105.321114
  55. 55.
    W.H. Richardson, Bayesian-based iterative method of image restoration. J. Opt. Soc. Am. 62, 55 (1972). doi:10.1364/JOSA.62.000055
  56. 56.
    L.B. Lucy, An iterative technique for the rectification of observed distributions. Astron. J. 79, 745–754 (1974). doi:10.1086/111605 ADSCrossRefGoogle Scholar
  57. 57.
    L.A. Shepp, Y. Vardi, Maximum likelihood reconstruction for emission tomography. IEEE Trans. Med. Imaging 1, 113 (1982). doi:10.1109/TMI.1982.4307558
  58. 58.
    T. Adye, Unfolding algorithms and tests using RooUnfold, in Proceedings, PHYSTAT 2011 Workshop on Statistical Issues Related to Discovery Claims in Search Experiments and Unfolding (Geneva, Switzerland, January 17–20, 2011), p. 313. doi:10.5170/CERN-2011-006, arXiv:1105.1160
  59. 59.
    B. Malaescu, An iterative, dynamically stabilized method of data unfolding, arXiv:0907.3791
  60. 60.
    ATLAS Collaboration, Measurement of three-jet production cross-sections in \(pp\) collisions at 7 TeV centre-of-mass energy using the ATLAS detector. Eur. Phys. J. C 75, 228 (2014). doi:10.1140/epjc/s10052-015-3363-3, arXiv:1411.1855
  61. 61.
    CMS Collaboration, First measurement of hadronic event shapes in \(pp\) collisions at \(\sqrt{(}s)=7\) TeV. Phys. Lett. B 699, 48 (2011). doi:10.1016/j.physletb.2011.03.060, arXiv:1102.0068
  62. 62.
    CMS Collaboration, Event shapes and azimuthal correlations in \(Z\) + jets events in pp collisions at \(\sqrt{s}=7\) TeV. Phys. Lett. B 722, 238 (2013). doi:10.1016/j.physletb.2013.04.025, arXiv:1301.1646
  63. 63.
    A. Höcker, V. Kartvelishvili, SVD approach to data unfolding. Nucl. Instrum. Meth. A 372, 469 (1996). doi:10.1016/0168-9002(95)01478-0, arXiv:hep-ph/9509307
  64. 64.
    S. Schmitt, TUnfold: an algorithm for correcting migration effects in high energy physics. JINST 7, T10003 (2012). doi:10.1088/1748-0221/7/10/T10003, arXiv:1205.6201
  65. 65.
    A. Kaur. Private communication. To be published in PhD thesisGoogle Scholar
  66. 66.
    A. Oehler, Strategy for an initial measurement of the inclusive jet cross section with the CMS detector. PhD thesis, Universität Karlsruhe, December, 2009Google Scholar
  67. 67.
    CMS Collaboration, Measurement of the double-differential inclusive jet cross section at \(\sqrt{s}\) = 13 TeV. Technical report, CMS-PAS-SMP-15-007, CERN (2015)Google Scholar
  68. 68.
    CMS Collaboration, Search for quark contact interactions and extra spatial dimensions using dijet angular distributions in proton-proton collisions at \(\sqrt{s} =\) 8 TeV. Phys. Lett. B 746, 79 (2015). doi:10.1016/j.physletb.2015.04.042, arXiv:1411.2646
  69. 69.
    P.C. Hansen, Analysis of discrete Ill-posed problems by means of the L-curve. SIAM Rev. 34, 561 (1992). doi:10.1137/1034115 MathSciNetCrossRefMATHGoogle Scholar
  70. 70.
    I. Volobouev, On the expectation-maximization unfolding with smoothing, arXiv:1408.6500
  71. 71.
    M. Kuusela, V.M. Panaretos, Statistical unfolding of elementary particle spectra: Empirical Bayes estimation and bias-corrected uncertainty quantification. doi:10.1214/15-AOAS857, arXiv:1505.04768
  72. 72.
    M. Kuusela, P.B. Stark, Shape-constrained uncertainty quantification in unfolding steeply falling elementary particle spectra, arXiv:1512.00905

Copyright information

© Springer International Publishing Switzerland 2017

Authors and Affiliations

  1. 1.Institute for Experimental Nuclear PhysicsKarlsruhe Institute of Technology (KIT)KarlsruheGermany

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