Speaker
Description
Trigger bandwidth limitations constrain physics analyses that target low-mass resonances, where high-rate data collection is essential. To circumvent this limitation Trigger-Level Analysis (TLA) can be applied. A recent publication by the ATLAS experiment demonstrated this approach during LHC Run 2 by processing a massive dataset of over 60 billion events, more than twice the number of fully reconstructed ATLAS events from Runs 1 and 2 combined. In the TLA workflow only fragments of complete collision events are stored, consisting of high-level objects (e.g. jets and photons) and limited additional information needed for calibration. This leads to a significant reduction in the event size and permits data acquisition at more than 20-fold rate compared to the standard approach. The TLA technique has been applied during Run 2 of the LHC to search for electroweak scale dijet resonances, extending the coverage of dark matter models to difficult to access phase space. This contribution reports the results of the Run 2 dijet TLA search . The operational performance of TLA trigger chains is emphasised along with an overview of the analysis strategies and computational constraints.
| Track | BSM-1: TeV Scale and prompt signatures |
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