Affiliation:
1. Institut für Hochenergiephysik der ÖAW, Nikolsdorfer Gasse 18, A-1050 Wien, Austria
Abstract
After a review of widely used pattern recognition methods we present the Kalman filter and the associated smoother as a recursive variant of conventional least squares estimators. We first discuss its application to the reconstruction of charged tracks, including simultaneous track finding and track fitting and a robustification of the filter. This section is concluded by a case study of track reconstruction strategy in the DELPHI experiment. The second part deals with vertex reconstruction, including the detection of outlying tracks. It is shown that the detection of secondary vertices can be further improved by a robustification of the vertex fit via the M-estimator.
Publisher
World Scientific Pub Co Pte Lt
Subject
Computational Theory and Mathematics,Computer Science Applications,General Physics and Astronomy,Mathematical Physics,Statistical and Nonlinear Physics
Cited by
7 articles.
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1. Physics and technology of time projection chambers as active targets;The European Physical Journal A;2018-10
2. Description and performance of track and primary-vertex reconstruction with the CMS tracker;Journal of Instrumentation;2014-10-16
3. Track and vertex reconstruction: From classical to adaptive methods;Reviews of Modern Physics;2010-05-07
4. The ‘LiC Detector Toy’ program;Journal of Physics: Conference Series;2008-07-01
5. The LiC detector toy program;Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment;2007-10