@article{913192,
      recid = {913192},
      author = {Braun, Nils.},
      title = {Combinatorial Kalman Filter and High Level Trigger  Reconstruction for the Belle II Experiment /},
      publisher = {Springer,},
      address = {Cham :},
      pages = {1 online resource (186 pages).},
      year = {2019},
      note = {"Doctoral thesis accepted by the Karlsruhe Institute of  Technology, Karlsruhe, Germany."--T.p.},
      abstract = {Combinatorial Kalman filters are a standard tool today for  pattern recognition and charged particle reconstruction in  high energy physics. In this thesis the implementation of  the track finding software for the Belle II experiment and  first studies on early Belle II data are presented. The  track finding algorithm exploits novel concepts such as  multivariate track quality estimates to form charged  trajectory hypotheses combining information from the Belle  II central drift chamber with the inner vertex  sub-detectors. The eventual track candidates show an  improvement in resolution on the parameters describing  their spatial and momentum properties by up to a factor of  seven over the former legacy implementation. The second  part of the thesis documents a novel way to determine the  collision event null time T0 and the implementation of  optimisation steps in the online reconstruction code, which  proved crucial in overcoming the high level trigger  limitations.},
      url = {http://library.usi.edu/record/913192},
      doi = {https://doi.org/10.1007/978-3-030-24},
}