Calorimeter Clustering Algorithms: Description and Performance
نویسندگان
چکیده
This note describes the performance of the calorimeter clustering algorithms used for ATLAS, and which provide inputs for particle identification. ATLAS uses two principal algorithms. The first is the “sliding-window” algorithm, which clusters calorimeter cells within fixed-size rectangles; results from this are used for electron, photon, and tau lepton identification. The second is the “topological” algorithm, which clusters together neighboring cells, as long as the signal in the cells is significant compared to noise. The results of this second algorithm are further used for jet and missing transverse energy reconstruction. This note first summarizes the steps of the calorimeter reconstruction software. A detailed description of the two clustering algorithms is then given. A last section summarizes their performance. The results presented in this note are obtained with the ATLAS ATHENA software releases 12 and 13.
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