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Volume 343 - Topical Workshop on Electronics for Particle Physics (TWEPP2018) - Systems, Planning, Installation, Commissioning and Running Experience
First performance measurements of the Fast Tracker Real Time Processor at ATLAS
N.V. Biesuz* on behalf of the ATLAS collaboration
*corresponding author
Full text: pdf
Pre-published on: 2019 May 21
Published on: 2019 July 25
Abstract
Real time track reconstruction at hadron colliders plays an important role in selecting 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. The Fast Tracker system
processes 64 eta-phi towers (partially overlapping), where 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 and 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.
DOI: https://doi.org/10.22323/1.343.0138
Open Access
Creative Commons LicenseCopyright owned by the author(s) under the term of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.