Speaker
Description
The ePIC dual-radiator Ring Imaging CHerenkov detector (dRICH) will serve as a particle identification (PID) system in the hadronic endcap of the experiment. Its main goals are to distinguish charged hadrons in the momentum range from 3 to 50 GeV/c and to assist in electron identification up to 15 GeV/c. To achieve these goals, it exploits Cherenkov radiation produced in two radiators—an aerogel and a C₂F₆ gas volume—to measure the particle velocity. Combined with momentum information, this allows the reconstruction of the particle mass and, consequently, its identification.
Cherenkov photons will be detected by approximately 320,000 silicon photomultipliers (SiPMs) operating at the single-photon threshold. Despite a dedicated cooling system maintaining the temperature at -40 °C, the dark count rate (DCR) remains non-negligible. Furthermore, radiation damage accumulated over the ePIC operational lifetime is expected to increase the DCR to as much as 300 kHz per channel, corresponding to a total of 96 GHz. This is significantly higher than the expected rate of physically relevant interactions, estimated to be around 500 kHz. The dRICH could reach a total data throughput of up to 1.4 Tbps, mostly composed of background signals.
Two strategies are under development to reduce this data volume: a machine learning-based data reduction algorithm implemented on the DAQ FPGA, and an Interaction Tagger, which flags the occurrence of actual particle passages through the detector. In this talk, I will present the latter approach. I will discuss how the addition of two layers of scintillating fibers (SciFi) in front of the dRICH can significantly reduce the data throughput by providing a fast interaction signal. The talk will cover the concept, the simulation studies, and the preliminary tests performed to assess the feasibility of the Interaction Tagger.
