Muon Detection in the ATLAS CSC Detector

The LHC and its participating experiments create a challenging data processing environment, characterized by a large amount of data in which only a small portion is expected to carry new scientific information. This publication addresses the problem of muon track detection in a cathode strip chamber (CSC), a component of the ATLAS Muon Spectrometer. A new algorithm, based on several novel ideas is introduced. The detect-before-estimate approach is presented, which first detects the muon track using a modified Hough transform, and then estimates the precise hit locations. The muon track detection is improved by taking into account additional, previously unused, information. It is shown that in the presence of high radiation background, the new detection procedure reduces the fake track identification rate significantly. For each track candidate, the hit cluster quality is calculated. It is then shown that including only good quality clusters in the track fitting algorithm, results in a better track parameter estimation. The algorithm is tested with real data taken from test beam, and evaluated using theoretical tools, especially developed for this problem.