Pattern Recognition and Reconstruction

Abstract

The topic of the chapter is track and vertex reconstruction in particle detectors. The reconstruction of (charged) tracks and the subsequent reconstruction of interaction vertices are important steps in the data analysis chain of an experiment in high-energy physics. Track reconstruction typically proceeds in three steps: Track Finding; Track Fitting; and Testing the track hypothesis. The most important pattern recognition algorithms and statistical estimation methods applied in this context are presented in the first section of the chapter, along with material on track-based alignment and formulas for the quick assessment of the momentum resolution of a tracking system. The following section deals with the reconstruction of interaction vertices, including both the primary interaction vertex in the collision zone of an experiment and secondary decay vertices of unstable particles. The pattern recognition methods and statical estimators involved are in many respects similar to the ones deployed in track reconstruction. The final section presents a brief overview of track and vertex reconstruction in the four LHC experiments. The methods applied by the experiments are described and their performance is illustrated by results from a few selected physics channels.