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@MASTERSTHESIS{Tayade:619739,
      author       = {Tayade, Akhilesh},
      othercontributors = {Behr, Katharina and Styles, Nicholas and Gregor,
                          Ingrid-Maria},
      title        = {{T}racking in {D}ense {E}nvironments for the{ATLAS} {IT}k
                      {S}trip {D}etector},
      school       = {University of Bonn},
      type         = {Masterarbeit},
      reportid     = {PUBDB-2024-07874},
      pages        = {77},
      year         = {2022},
      note         = {Masterarbeit, University of Bonn, 2022},
      abstract     = {The Phase II upgrade of the ATLAS detector will prepare it
                      to handle the 2.5–fold increase in instantaneous
                      luminosity of the High Luminosity LHC project starting in
                      2028. The upgrade will also involve the tracking sub-system
                      of the ATLAS detector to be replaced by the Inner Tracker
                      (ITk), which is made up of a closer-to-beam-line Pixel and
                      acircumscribing Strip detector. A particular challenge in
                      such a scenario is the reconstruction of highly collimated
                      particle trajectories that overlap and share hits in the
                      ITk. These Dense Environments are ubiquitous since they
                      occur in the cores of high pT jets. The reconstruction of
                      such high pT jets is important to identify boosted objects
                      like highly energetic top quarks or Higgs bosons. These
                      objects are of key importance, for example, in searches for
                      di-Higgs production, the observation of which is one of the
                      central goals of HL-LHC.In the ATLAS software for the
                      current Inner Detector (ID), merged clusters in the pixel
                      detector, resulting from energy deposits of several close-by
                      particles are identified and split using deep neural nets.
                      No such splitting procedure is used for the strip part of
                      the current ID. The necessity of such methods is unclear for
                      the ITk given its superior resolution compared to the
                      current ID. Previous results show that for the ID, the
                      reconstruction efficiency decreases significantly in jet
                      cores with increase of jet pT .In this thesis, first, the
                      performance of cluster and track reconstruction in dense
                      environments is studied for the ITk Strip detector. The goal
                      is to determine if a cluster splitting procedure is needed.
                      The relevant variables sensitive to cluster merging such as
                      cluster size, track merging rates, residual and impact
                      parameter resolution, etc. are studied. It is found that
                      tracks in high-pT jet cores have a high merging rate and
                      suffer from a drop in track reconstruction efficiency as the
                      jet pT increases, suggesting a need for improvement of the
                      track reconstructionsoftware for dense environments.Second,
                      a truth-based cluster splitting, wherein, truth information
                      about the particles is used to identify the positions and
                      their uncertainties of the sub-clusters belonging to the
                      individual particles contributing to a merged cluster, is
                      being implemented. This will allow for the evaluation of the
                      reconstruction performance of the ATLAS tracking software in
                      case of a perfect splitting of multi-particle clusters and
                      hence an estimation of the potential gain from implementing
                      a machine learning based splitting at the reconstruction
                      level. Based onthe outcome of the idealized splitting, a
                      procedure similar to the one implemented for the ID Pixel
                      detector can be adopted in the future.},
      cin          = {ATLAS},
      cid          = {I:(DE-H253)ATLAS-20120731},
      pnm          = {611 - Fundamental Particles and Forces (POF4-611)},
      pid          = {G:(DE-HGF)POF4-611},
      experiment   = {EXP:(DE-H253)LHC-Exp-ATLAS-20150101},
      typ          = {PUB:(DE-HGF)19},
      url          = {https://bib-pubdb1.desy.de/record/619739},
}