ATLAS Reconstruction and Performance

  • Steven SchrammEmail author
Part of the Springer Theses book series (Springer Theses)


When conducting an analysis, the first step is to define the topology that will be considered. This selection typically requires the presence or absence of certain objects, where an object is either a physical particle (electrons, muons, taus, photons), a representation of an underlying physical process (jets and b-jets), or the contribution of invisible processes creating an imbalance in the event (\(\mathrm {E}_{\mathrm {T}}^{\mathrm {miss}}\)). As such, detector quantities such as cells, tracks, and clusters must be translated into objects, which can then be properly calibrated and used in analyses.


Transverse Energy Detector Track Electromagnetic Calorimeter Muon Track Muon Spectrometer 
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.


  1. 1.
    ATLAS Collaboration, Electron and photon energy calibration with the ATLAS detector using LHC Run 1 data. Eur. Phys. J. C 74(10), 3071 (2014). arXiv:1407.5063
  2. 2.
    W. Lamp et al., Calorimeter clustering algorithms: description and performance. Technical report, ATL-LARG-PUB-2008-002, CERN, Geneva, Apr 2008Google Scholar
  3. 3.
    ATLAS Collaboration, Measurements of the photon identification efficiency with the ATLAS detector using 4.9 fb\(^{-1}\) of pp collision data collected in 2011. Technical report, ATLAS-CONF-2012-123, CERN, Geneva, Aug 2012Google Scholar
  4. 4.
    ATLAS Collaboration, Measurement of the inclusive isolated prompt photon cross section in \(pp\) collisions at \(\sqrt{s}=7\) TeV with the ATLAS detector. Phys. Rev. D 83, 052005 (2011). arXiv:1012.4389
  5. 5.
    ATLAS Collaboration, Electron performance measurements with the ATLAS detector using the 2010 LHC proton–proton collision data. Eur. Phys. J. 72, 1909 (2012). arXiv:1110.3174 [hep-ex]
  6. 6.
    ATLAS Collaboration, Measurement of the muon reconstruction performance of the ATLAS detector using 2011 and 2012 LHC proton–proton collision data. Eur. Phys. J. C 74(11), 3130 (2014). arXiv:1407.3935 [hep-ex]
  7. 7.
    Particle Data Group Collaboration, K. Olive et al., Review of particle physics. Chin. Phys. C 38, 090001 (2014)Google Scholar
  8. 8.
    ATLAS Collaboration, Search for dark matter in events with heavy quarks and missing transverse momentum in \(pp\) collisions with the ATLAS detector. Eur. Phys. J. C 75(2), 92 (2015). arXiv:1410.4031 [hep-ex]
  9. 9.
    ATLAS Collaboration, Calibration of \(b\)-tagging using dileptonic top pair events in a combinatorial likelihood approach with the ATLAS experiment. Technical report, ATLAS-CONF-2014-004, CERN, Geneva, Feb 2014Google Scholar
  10. 10.
    ATLAS Collaboration, Performance of missing transverse momentum reconstruction in proton–proton collisions at 7 TeV with ATLAS. Eur. Phys. J. C 72, 1844 (2012). arXiv:1108.5602 [hep-ex]
  11. 11.
    ATLAS Collaboration, Performance of missing transverse momentum reconstruction in ATLAS studied in proton–proton collisions recorded in 2012 at 8 TeV. Technical report, ATLAS-CONF-2013-082, CERN, Geneva, Aug 2013Google Scholar

Copyright information

© Springer International Publishing Switzerland 2017

Authors and Affiliations

  1. 1.Section de PhysiqueUniversity of GenevaGenevaSwitzerland

Personalised recommendations