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Associated jet and subjet rates in light-quark and gluon jet discrimination

  • Biplob Bhattacherjee
  • Satyanarayan Mukhopadhyay
  • Mihoko M. Nojiri
  • Yasuhito Sakaki
  • Bryan R. Webber
Open Access
Regular Article - Theoretical Physics

Abstract

We show that in studies of light quark- and gluon-initiated jet discrimination, it is important to include the information on softer reconstructed jets (associated jets) around a primary hard jet. This is particularly relevant while adopting a small radius parameter for reconstructing hadronic jets. The probability of having an associated jet as a function of the primary jet transverse momentum (p T ) and radius, the minimum associated jet p T and the association radius is computed up to next-to-double logarithmic accuracy (NDLA), and the predictions are compared with results from Herwig++, Pythia6 and Pythia8 Monte Carlos (MC). We demonstrate the improvement in quark-gluon discrimination on using the associated jet rate variable with the help of a multivariate analysis. The associated jet rates are found to be only mildly sensitive to the choice of parton shower and hadronization algorithms, as well as to the effects of initial state radiation and underlying event. In addition, the number of k t subjets of an anti-k t jet is found to be an observable that leads to a rather uniform prediction across different MC’s, broadly being in agreement with predictions in NDLA, as compared to the often used number of charged tracks observable.

Keywords

QCD Phenomenology Jets 

Notes

Open Access

This article is distributed under the terms of the Creative Commons Attribution License (CC-BY 4.0), which permits any use, distribution and reproduction in any medium, provided the original author(s) and source are credited.

References

  1. [1]
    J. Gallicchio and M.D. Schwartz, Quark and Gluon Tagging at the LHC, Phys. Rev. Lett. 107 (2011) 172001 [arXiv:1106.3076] [INSPIRE].ADSCrossRefGoogle Scholar
  2. [2]
    J. Gallicchio et al., Multivariate discrimination and the Higgs + W/Z search, JHEP 04 (2011) 069 [arXiv:1010.3698] [INSPIRE].ADSCrossRefGoogle Scholar
  3. [3]
    J. Gallicchio and M.D. Schwartz, Quark and Gluon Jet Substructure, JHEP 04 (2013) 090 [arXiv:1211.7038] [INSPIRE].ADSCrossRefGoogle Scholar
  4. [4]
    A.J. Larkoski, G.P. Salam and J. Thaler, Energy Correlation Functions for Jet Substructure, JHEP 06 (2013) 108 [arXiv:1305.0007] [INSPIRE].ADSMathSciNetCrossRefMATHGoogle Scholar
  5. [5]
    A.J. Larkoski, J. Thaler and W.J. Waalewijn, Gaining (Mutual) Information about Quark/Gluon Discrimination, JHEP 11 (2014) 129 [arXiv:1408.3122] [INSPIRE].ADSCrossRefGoogle Scholar
  6. [6]
    ATLAS collaboration, Light-quark and gluon jet discrimination in pp collisions at \( \sqrt{s} \) = 7 TeV with the ATLAS detector, Eur. Phys. J. C 74 (2014) 3023 [arXiv:1405.6583] [INSPIRE].ADSGoogle Scholar
  7. [7]
    CMS collaboration, Performance of quark/gluon discrimination in 8 TeV pp data, CMS-PAS-JME-13-002 (2013).
  8. [8]
    M. Dasgupta, L. Magnea and G.P. Salam, Non-perturbative QCD effects in jets at hadron colliders, JHEP 02 (2008) 055 [arXiv:0712.3014] [INSPIRE].ADSCrossRefGoogle Scholar
  9. [9]
    G.P. Salam, Towards Jetography, Eur. Phys. J. C 67 (2010) 637 [arXiv:0906.1833] [INSPIRE].ADSCrossRefGoogle Scholar
  10. [10]
    S. Catani, Y.L. Dokshitzer, M. Olsson, G. Turnock and B.R. Webber, New clustering algorithm for multi - jet cross-sections in e + e annihilation, Phys. Lett. B 269 (1991) 432 [INSPIRE].ADSCrossRefGoogle Scholar
  11. [11]
    S. Catani, Y.L. Dokshitzer, M.H. Seymour and B.R. Webber, Longitudinally invariant K t clustering algorithms for hadron hadron collisions, Nucl. Phys. B 406 (1993) 187 [INSPIRE].ADSCrossRefGoogle Scholar
  12. [12]
    S.D. Ellis and D.E. Soper, Successive combination jet algorithm for hadron collisions, Phys. Rev. D 48 (1993) 3160 [hep-ph/9305266] [INSPIRE].ADSGoogle Scholar
  13. [13]
    M. Cacciari, G.P. Salam and G. Soyez, The Anti-k(t) jet clustering algorithm, JHEP 04 (2008) 063 [arXiv:0802.1189] [INSPIRE].ADSCrossRefMATHGoogle Scholar
  14. [14]
    Y.L. Dokshitzer, G.D. Leder, S. Moretti and B.R. Webber, Better jet clustering algorithms, JHEP 08 (1997) 001 [hep-ph/9707323] [INSPIRE].ADSCrossRefGoogle Scholar
  15. [15]
    M. Wobisch and T. Wengler, Hadronization corrections to jet cross-sections in deep inelastic scattering, hep-ph/9907280 [INSPIRE].
  16. [16]
    M. Wobisch, Measurement and QCD analysis of jet cross sections in deep-inelastic positron proton collisions at \( \sqrt{s} \) = 300 GeV, DESY-THESIS-2000-049 [INSPIRE].
  17. [17]
    E. Gerwick, S. Schumann, B. Gripaios and B. Webber, QCD Jet Rates with the Inclusive Generalized kt Algorithms, JHEP 04 (2013) 089 [arXiv:1212.5235] [INSPIRE].ADSCrossRefGoogle Scholar
  18. [18]
    E. Gerwick and P. Schichtel, Jet properties at high-multiplicity, arXiv:1412.1806 [INSPIRE].
  19. [19]
    K. Konishi, A. Ukawa and G. Veneziano, Jet Calculus: A Simple Algorithm for Resolving QCD Jets, Nucl. Phys. B 157 (1979) 45 [INSPIRE].ADSMathSciNetCrossRefGoogle Scholar
  20. [20]
    Y.L. Dokshitzer, V.A. Khoze, A.H. Mueller and S.I. Troian, Basics of perturbative QCD, Gif-sur-Yvette, France: Ed. Frontieres (1991).Google Scholar
  21. [21]
    R.K. Ellis, W.J. Stirling and B.R. Webber, QCD and collider physics, Camb. Monogr. Part. Phys. Nucl. Phys. Cosmol. 8 (1996) 1 [INSPIRE].Google Scholar
  22. [22]
    M. Bahr et al., HERWIG++ Physics and Manual, Eur. Phys. J. C 58 (2008) 639 [arXiv:0803.0883] [INSPIRE].ADSCrossRefGoogle Scholar
  23. [23]
    T. Sjöstrand, S. Mrenna and P.Z. Skands, A Brief Introduction to PYTHIA 8.1, Comput. Phys. Commun. 178 (2008) 852 [arXiv:0710.3820] [INSPIRE].ADSCrossRefMATHGoogle Scholar
  24. [24]
    T. Sjöstrand et al., An Introduction to PYTHIA 8.2, Comput. Phys. Commun. 191 (2015) 159 [arXiv:1410.3012] [INSPIRE].ADSCrossRefMATHGoogle Scholar
  25. [25]
    J. Pumplin et al., New generation of parton distributions with uncertainties from global QCD analysis, JHEP 07 (2002) 012 [hep-ph/0201195] [INSPIRE].ADSCrossRefGoogle Scholar
  26. [26]
    A. Sherstnev and R.S. Thorne, Different PDF approximations useful for LO Monte Carlo generators, arXiv:0807.2132 [INSPIRE].
  27. [27]
    S. Ovyn, X. Rouby and V. Lemaitre, DELPHES, a framework for fast simulation of a generic collider experiment, arXiv:0903.2225 [INSPIRE].
  28. [28]
    M. Cacciari, G.P. Salam and G. Soyez, FastJet User Manual, Eur. Phys. J. C 72 (2012) 1896 [arXiv:1111.6097] [INSPIRE].ADSCrossRefGoogle Scholar
  29. [29]
    M. Cacciari and G.P. Salam, Dispelling the N 3 myth for the k t jet-finder, Phys. Lett. B 641 (2006) 57 [hep-ph/0512210] [INSPIRE].ADSCrossRefGoogle Scholar
  30. [30]
    T. Sjöstrand, S. Mrenna and P.Z. Skands, PYTHIA 6.4 Physics and Manual, JHEP 05 (2006) 026 [hep-ph/0603175] [INSPIRE].ADSCrossRefMATHGoogle Scholar
  31. [31]
    D. Bertolini, T. Chan and J. Thaler, Jet Observables Without Jet Algorithms, JHEP 04 (2014) 013 [arXiv:1310.7584] [INSPIRE].ADSCrossRefGoogle Scholar
  32. [32]
    A.J. Larkoski, D. Neill and J. Thaler, Jet Shapes with the Broadening Axis, JHEP 04 (2014) 017 [arXiv:1401.2158] [INSPIRE].ADSCrossRefGoogle Scholar
  33. [33]
    A. Hocker et al., TMVA - Toolkit for Multivariate Data Analysis, PoS ACAT (2007) 040 [physics/0703039] [INSPIRE].
  34. [34]
    P. Speckmayer, A. Hocker, J. Stelzer and H. Voss, The toolkit for multivariate data analysis, TMVA 4, J. Phys. Conf. Ser. 219 (2010) 032057 [INSPIRE].CrossRefGoogle Scholar
  35. [35]
  36. [36]
    P. Bolzoni, B.A. Kniehl and A.V. Kotikov, Gluon and quark jet multiplicities at N 3 LO + NNLL, Phys. Rev. Lett. 109 (2012) 242002 [arXiv:1209.5914] [INSPIRE].ADSCrossRefGoogle Scholar
  37. [37]
    P. Bolzoni, B.A. Kniehl and A.V. Kotikov, Average gluon and quark jet multiplicities at higher orders, Nucl. Phys. B 875 (2013) 18 [arXiv:1305.6017] [INSPIRE].ADSMathSciNetCrossRefMATHGoogle Scholar

Copyright information

© The Author(s) 2015

Authors and Affiliations

  • Biplob Bhattacherjee
    • 1
  • Satyanarayan Mukhopadhyay
    • 2
  • Mihoko M. Nojiri
    • 2
    • 3
  • Yasuhito Sakaki
    • 3
  • Bryan R. Webber
    • 4
  1. 1.Centre for High Energy PhysicsIndian Institute of ScienceBangaloreIndia
  2. 2.Kavli IPMU (WPI)The University of TokyoKashiwaJapan
  3. 3.KEK Theory Center and Sokendai,TsukubaJapan
  4. 4.Cavendish LaboratoryCambridgeUnited Kingdom

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