Advertisement

\(\mathrm{{D}}^\mathbf {0}\rightarrow \mathrm{{K}}^\mathbf {-}{\pi }^\mathbf {+}\) Decay Reconstruction

  • Andrea FestantiEmail author
Chapter
Part of the Springer Theses book series (Springer Theses)

Abstract

The chapter is devoted to the description of the \(\mathrm{D^0}\) analysis in Pb–Pb and p–Pb collisions. The aim of the analysis is to extract the elements that are needed to measure the elliptic flow in Pb–Pb collisions, the production cross section and nuclear modification factor in both Pb–Pb and p–Pb collisions. In the first part of the chapter, Sect. 5.1, the Pb–Pb and p–Pb data samples are described. In Sect. 5.2 the event-plane determination for the azimuthal anisotropy measurement is explained. Section 5.3 is devoted to the description of the reconstruction and selection strategy for D mesons. The strategy exploits the displacement (from the primary vertex) of the secondary vertices originating from the weak decay of the D mesons. The variables allowing to select the \({\mathrm{D^0}\rightarrow \mathrm{K}^-{\pi }^+}\) topology will be introduced, together with the particle identification procedure to improve the rejection of the combinatorial background. A description of the invariant mass analysis used to extract the yields is given in Sect. 5.4. The invariant mass distributions together with the fits performed to obtain the raw signals are shown for both Pb–Pb and p–Pb systems. Section 5.5 describes the study of the \(\mathrm{D^0}\) reflections, defined as the signal candidates that pass the cuts both as \(\mathrm{D^0}\) and \(\overline{\mathrm{D^0}}\). The last two Sects. 5.6 and 5.7, are devoted to the description of the efficiency calculation and feed-down correction, respectively.

Keywords

Invariant Mass Distribution Primary Vertex Centrality Class Secondary Vertex Elliptic Flow 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    M.L. Miller, K. Reygers, S. J. Sanders, P. Steinberg, Glauber Modeling in High-Energy Nuclear Collisions. Ann. Rev. Nucl. Part. Sci. 57 205–243 (2007). arXiv:nucl-ex/0701025 [nucl-ex]
  2. 2.
    ALICE Collaboration, B. Abelev et al., Centrality determination of Pb–Pb collisions at \(\sqrt{s_{\rm NN}}=2.76\) TeV with ALICE. Phys. Rev. C 88, 044909 (2013)Google Scholar
  3. 3.
    ALICE Collaboration, B. Abelev et al., Azimuthal anisotropy of D Meson production in Pb–Pb collisions at \(\sqrt{s_{\rm NN}} = 2.76\) TeV. Phys. Rev. C 90, 034904 (2014). arXiv:1405.2001 [nucl-ex]
  4. 4.
    Particle Data Group Collaboration, K. Olive et al., Review of particle physics. Chin. Phys. C 38, 090001 (2014)Google Scholar
  5. 5.
    A. Dainese, Charm Production and In-Medium QCD Energy Loss in Nucleus–Nucleus Collisions with ALICE: A Performance Study. arXiv:nucl-ex/0311004 [nucl-ex]
  6. 6.
    F. James, M. Winkler, Minuit User’s Guide. http://seal.web.cern.ch/seal/documents/minuit/mnusersguide.pdf
  7. 7.
    ALICE collaboration, B. Abelev et al., Pseudorapidity density of charged particles in p–Pb collisions at \(\sqrt{s_{\rm NN}}=5.02\) TeV. Phys. Rev. Lett. 110, 032301 (2013)Google Scholar
  8. 8.
    ALICE collaboration, B. Abelev et al., Transverse momentum distribution and nuclear modification factor of charged particles in p–Pb collisions at \(\sqrt{s_{\rm NN}}=5.02\) TeV. Phys. Rev. Lett. 110 082302 (2013). arXiv:1210.4520 [nucl-ex]
  9. 9.
    Brun, R., Carminati, F., Giani, S.: GEANT Detector Description and Simulation ToolGoogle Scholar
  10. 10.
    X.-N. Wang, M. Gyulassy, HIJING: a monte carlo model for multiple jet production in pp, pA and AA collisions. Phys. Rev. D 44, 3501–3516 (1991)ADSCrossRefGoogle Scholar
  11. 11.
    T. Sjostrand, S. Mrenna, P.Z. Skands, PYTHIA 6.4 Physics and Manual. JHEP 0605, 026 (2006). arXiv:hep-ph/0603175 [hep-ph]
  12. 12.
    P.Z. Skands, Tuning monte carlo generators: the perugia tunes. Phys. Rev. D 82, 074018 (2010). arXiv:1005.3457 [hep-ph]ADSCrossRefGoogle Scholar
  13. 13.
    M. Cacciari, M. Greco, P. Nason, The \(p_{\rm T}\) spectrum in heavy-flavor hadroproduction. JHEP 9805, 007 (1998). arXiv:hep-ph/9803400 [hep-ph]ADSCrossRefGoogle Scholar
  14. 14.
    M. Cacciari, S. Frixione, P. Nason, The \(p_{\rm T}\) spectrum in heavy-flavor photoproduction. JHEP 0103, 006 (2001). arXiv:hep-ph/0102134 [hep-ph]ADSCrossRefGoogle Scholar
  15. 15.
    M. Cacciari, S. Frixione, N. Houdeau, M.L. Mangano, P. Nason et al., Theoretical predictions for charm and bottom production at the LHC. JHEP 1210, 137 (2012). arXiv:1205.6344 [hep-ph]ADSCrossRefGoogle Scholar
  16. 16.
    D. Lange, The EvtGen particle decay simulation package. Nucl. Instrum. Meth. A 462, 152–155 (2001)ADSCrossRefGoogle Scholar
  17. 17.
    M.L. Mangano, P. Nason, G. Ridolfi, Heavy-Quark correlations in hadron collisions at next-to-leading order. Nucl. Phys. B 373, 295–345 (1992)ADSCrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Department of Physics, INFN-Sezione di PadovaUniversità degli Studi di PadovaPaduaItaly

Personalised recommendations