Pattern recognition in a high-rate GEM-TPC

A pattern recognition software for a continuously operating high-rate Time Projection Chamber with Gas Electron Multiplier amplification (GEM-TPC) has been designed and tested. Space points are delivered by a track-independent clustering algorithm. A true 3-dimensional track follower combines them to helical tracks, without constraints on the vertex position. Fast helix fits, based on a conformal mapping on the Riemann sphere, are the basis for deciding whether points belong to one track. To assess the performance of the algorithm in a high-rate environment, pp interactions at a rate of 2 × 10⁷ s⁻¹, the maximum rate foreseen for PANDA, have been simulated. The pattern recognition is capable of finding different kinds of track topologies with high efficiency and provides excellent seed values for track fitting or online event selection. The feasibility of event deconvolution has been demonstrated: Different techniques to retain the tracks from an event with known time from other tracks in the TPC are presented in this paper.