Iterative Retina for High Track Multiplicity in a Barrel-Shaped Tracker and High Magnetic Field

Real-time track tracking in high energy physics experiments at colliders running luminosity is very challenging for trigger systems. To perform pattern-recognition and fitting online system, the artificial Retina algorithm has been introduced field. can be implemented state of art FPGA devices. Our developments use an iterative way to identify barrel-shape tracker embedded a magnetic field with multiplicity. As benchmark we simulate LHC t-tbar events, pile-up 200 GEANT-4 based simulation 6-layers barrel detector made silicon modules. With this sample performance hardware design (resource usage, latency) evaluated. Both efficiency purity are over 90%. Moreover have also added Kalman filter after fit improve resolution on parameters. results show that work well together find through event provides resolutions reconstructed