Speaker
Stefano Franchellucci
(Universite de Geneve (CH))
Description
A number of flagship analyses in the ATLAS experiment rely on real-time b-tagging to efficiently record data. In run 3, the jet and b-jet trigger was updated with state of the art machine learning, to reduce background rates and improve efficiency, while remaining within the constraints of the trigger hardware. We will discuss the design, optimization, deployment, and validation of the ATLAS run 3 b-jet triggers, and their impact several important physics analyses.
Author
Stefano Franchellucci
(Universite de Geneve (CH))
