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@INPROCEEDINGS{Krger:472251,
      author       = {Kröger, Jens and Huth, Lennart},
      title        = {{E}fficient {A}nalysis of {T}est-beam {D}ata with the
                      {C}orryvreckan {F}ramework},
      volume       = {34},
      publisher    = {Journal of the Physical Society of Japan},
      reportid     = {PUBDB-2021-04950},
      series       = {JPS Conference Proceedings},
      pages        = {010024},
      year         = {2021},
      comment      = {Proceedings of the 29th International Workshop on Vertex
                      Detectors (VERTEX2020) - Journal of the Physical Society of
                      Japan, 2021. - ISBN 4-89027-147-3 -
                      doi:10.7566/JPSCP.34.010024},
      booktitle     = {Proceedings of the 29th International
                       Workshop on Vertex Detectors
                       (VERTEX2020) - Journal of the Physical
                       Society of Japan, 2021. - ISBN
                       4-89027-147-3 -
                       doi:10.7566/JPSCP.34.010024},
      abstract     = {Stringent requirements are posed on the next generations of
                      vertex and tracking detectors for high-energy physics
                      experiments to reach the foreseen physics goals. A large
                      variety of silicon pixel sensors targeting the specific
                      needs of each use case are developed and tested both in
                      laboratory and test-beam measurement campaigns. Corryvreckan
                      is a flexible, fast and lightweight test-beam data
                      reconstruction and analysis framework based on a modular
                      concept of the reconstruction chain. It is designed to
                      fulfil the requirements for offline event building in
                      complex data-taking environments combining detectors with
                      different readout schemes. Its modular architecture
                      separates the framework core from the implementation of
                      reconstruction, analysis and detector specific algorithms.
                      In this paper, a brief overview of the software framework
                      and the reconstruction and analysis chain is provided. This
                      is complemented by an example analysis of a data set using
                      the offline event building capabilities of the framework and
                      an improved event building scheme allowing for a more
                      efficient usage of test-beam data exploiting the pivot pixel
                      information of the Mimosa26 sensors.},
      month         = {Oct},
      date          = {2020-10-05},
      organization  = {International Workshop on Vertex
                       Detectors , Tsukuba (Japan (Online)), 5
                       Oct 2020 - 8 Oct 2020},
      cin          = {FHTestBeam / ATLAS},
      cid          = {I:(DE-H253)FHTestBeam-20150203 / I:(DE-H253)ATLAS-20120731},
      pnm          = {623 - Data Management and Analysis (POF4-623)},
      pid          = {G:(DE-HGF)POF4-623},
      experiment   = {EXP:(DE-H253)TestBeamline21-20150101},
      typ          = {PUB:(DE-HGF)8 / PUB:(DE-HGF)7},
      doi          = {10.7566/JPSCP.34.010024},
      url          = {https://bib-pubdb1.desy.de/record/472251},
}