• Nils BraunEmail author
Part of the Springer Theses book series (Springer Theses)


The following chapter summarizes the basic mathematical and algorithmic foundations used throughout this thesis. The goal is to present the topics to a level of detail which helps to understand the work presented in the following chapters. For a more complete and thorough discussion, references on further reading are given in each section.


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    Gelb MJ (2018) Search for the rare decay B+ to l+ nu gamma with the full event interpretation at the Belle experiment. PhD thesis, KIT.,
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    Keck T, Abudinen F, Bernlochner FU, Cheaib R et al (Jul 2018) The full event interpretation—an exclusive tagging algorithm for the Belle II experiment. arXiv:1807.08680
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    Braun N (2015) Momentum estimation of slow pions and improvements on the track finding in the central drift chamber for the Belle II experiment. Master’s thesis, KIT.
  4. 4.
    Trusov V (2016) Development of pattern recognition algorithms for the central drift chamber of the Belle II detector. PhD thesis, KIT.
  5. 5.
    Alexopoulos T, Bachtis M, Gazis E, Tsipolitis G (2008) Implementation of the legendre transform for track segment reconstruction in drift tube chambers. Nucl Instrum Methods Phys Res Sect Accel Spectrometers Detect Assoc Equip 592(3):456–462., Scholar
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    Hough PVC (1962) Method and means for recognizing complex patterns. Patent.
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    Frost O (2013) A local tracking algorithm for the central drift chamber of Belle II. Master’s thesis, KIT.
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    Toffoli T, Margolus N (1987) Cellular automata machines: a new environment for modeling. MIT Press.
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    Abt I, Emeliyanov D, Kisel I, Masciocchi S (2002) CATS: a cellular automaton for tracking in silicon for the HERA-B vertex detector. Nucl Instrum Methods Phys Res Sect A Accel Spectrometers Detect Assoc Equip 489(1–3):389–405., Scholar
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    Wagner J (2017) Track finding with the silicon strip detector of the Belle II experiment. Master’s thesis, KIT.
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    Aimonen P (2011) Basic concept of Kalman filtering.
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    Frühwirth R, Strandlie A (1999) Track fitting with ambiguities and noise: a study of elastic tracking and nonlinear filters. Comput Phys Commun 120(2–3):197–214., Scholar
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    Keck T (2017) FastBDT: a speed-optimized multivariate classification algorithm for the Belle II experiment. Comput Softw Big Sci 1(1):2. arXiv:1609.06119,,
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Authors and Affiliations

  1. 1.ETPKarlsruhe Institute of TechnologyKarlsruheGermany

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