Speaker
Finn Jonathan Labe
(Universität Hamburg)
Description
At the CMS experiment, a two-layer trigger system is used to decide which collision events to store for later analysis. Due to the large number of low energy collisions at the LHC, currently used triggers often rely on momentum thresholds, only triggering on events with at least one highly energetic object. In searches for certain signatures, this leads to potentially relevant events being discarded in the trigger system. Novel techniques, utilizing machine learning inside the first hardware layer of the trigger, are studied to recover this phase space. Instead of individual objects, these triggers rely on the full event topology to trigger on previously inaccessible events.
Primary author
Finn Jonathan Labe
(Universität Hamburg)
Co-authors
Artur Lobanov
(Universität Hamburg)
Gregor Kasieczka
(UNI/EXP (Uni Hamburg, Institut fur Experimentalphysik))
Johannes Haller
(Institut für Experimentalphysik, Universität Hamburg)
Matthias Schroeder
(Universität Hamburg)
