Speaker
Description
The Compressed Baryonic Matter experiment (CBM) at FAIR is designed to explore the QCD phase diagram at high baryon densities with interaction rates up to 10 MHz using triggerless free-streaming data acquisition. The CBM Ring Imaging Cherenkov detector (RICH) contributes to the overall PID by identification of electrons from the lowest momenta up to 6-8 GeV/c, with a pion suppression factor of more than 100. The RICH reconstruction combines a standalone (trackless) Cherenkov ring-finding with a ring-track matching of extrapolated tracks from the Silicon Tracking System (STS) by closest distance.
The ring reconstruction is particularly challenging due to high ring multiplicity regions, smeared ring structures and varying radii & hits per ring. Hence, an alternative pattern-aware ring-finding approach based on a graph neural network is investigated for the CBM RICH. The end-to-end pipeline performs ring instance reconstruction using 2+1 dimensional information of hits (2D position and time) as input. In addition to ring reconstruction, noise classification is included as an auxiliary downstream task.