Speakers
Description
Jets containing b-hadrons (b-jets) are a key signature to trigger events at collider experiments, as they're associated to many interesting physics processes, such as Higgs decays. Charged particle tracks reconstruction, the main input for b-tagging algorithms, makes the b-jet trigger selections some of the most CPU intensive ones at the ATLAS High-Level-Trigger (HLT). To cope with the real-time constraints and enhance the physics reach of the collected data, new trigger strategies were developed for the start of the LHC Run 3, involving Machine Learning (ML) techniques. The success of these strategies in the first years of LHC Run 3 data-taking encouraged the development of new algorithms to achieve better performances in HLT b-tagging for 2024 data-taking. The Run-3 b-jet trigger developments will be presented, as well their first performance assessment in LHC data and some possible future upgrades.
