First performance measurements of the Fast Tracker Real Time Processor at ATLAS

Real time track reconstruction at hadron colliders is one of the most powerful tools to select interesting events from the huge background while mitigating the effect of pile-up. The Fast Tracker, an upgrade to the current ATLAS trigger system, will feed the High Level Trigger with high quality tracks reconstructed over the entire detector at 100 kHz rate. This is accomplished by dividing the detector into 64 η−ϕ towers. Each tower is processed by a dedicated asynchronous, data-driven pipeline. The combinatorial challenge inherent to tracking is solved with the use of Associative Memory ASICs that compare inner detector hits to millions of pre-calculated patterns simultaneously. The tracking problem within matched patterns is further simplified by using pre-computed linearized fitting constants and leveraging fast digital signal processing in modern commercial FPGAs. Half of the system has been produced and integration in ATLAS is proceeding to demonstrate functionality with real data with a partial detector coverage. We show the first results on system performance studies. Tracks were reconstructed and validated with Fast Tracker functional simulation. The system integration in the ATLAS experiment is progressing through 2018 to reach stable track processing. These studies will continue by evaluating the Fast Tracker tracking resolution and latency on real data. Those measurements will allow optimization of the system improving its performance. We report results of this first important experience with data in preparation of the full Fast Tracker operational conditions in 2021.