Track propagation methods for the correlation of charged tracks with clusters in the calorimeter of the $\overline{P}$ANDA experiment

To classify clusters of hits in the electromagnetic calorimeter (EMC) of $\overline{P}$ANDA (antiProton ANnihilation at DArmstadt), one has to match these EMC clusters with tracks of charged particles reconstructed from hits in the tracking system. Therefore the tracks are propagated to the surface of the EMC and associated with EMC clusters which are nearby and below a cut parameter. In this work, we propose a helix propagator to extrapolate the track from the Straw Tube Tracker (STT) to the inner surface of the EMC instead of the GEANE propagator which is already embedded within the PandaRoot computational framework. The results for both propagation methods show a similar quality, with a 30% gain in CPU time when using the helix propagator. We use Monte-Carlo truth information to compare the particle ID of the EMC clusters with the ID of the extrapolated points, thus deciding upon the correctness of the matches. By varying the cut parameter as a function of transverse momentum and particle type, our simulations show that the purity can be increased by 3–5% compared to the default value which is a constant cut in the $\overline{P}$ANDA simulation framework PandaRoot.