Speaker
Description
Traditional searches for new physics at the ATLAS experiment can be limited by the finite trigger bandwidth and storage capacity for LHC collision data. The ATLAS trigger determines which data to discard and selects only a small fraction of events for further analysis. In order to study events that are typically rejected by the trigger ATLAS has introduced a new real-time data analysis technique: Trigger Level Analysis (TLA). TLA provides a huge increase in statistics as the memory footprint of each collision decreases from around 1MB to 6.5kB per event.
This facilitates the search for new physics in previously unexplored regions of phase space and increases the sensitivity reach to dark matter models with low masses and couplings. This contribution introduces TLA in ATLAS for LHC Run 3 and presents its potential applications.
