The increasing track multiplicity in ATLAS poses new challenges for primary vertex reconstruction software, where it is expected to reach over 70 inelastic proton-proton collisions per beam crossing during Run-2 of the LHC and even more extreme vertex density in the next upcoming Runs.
In order to address these challenges, two new tools were adapted.
The first is the Gaussian track density seed finder, a simple yet powerful analytic model of the track density along the beam axis in order to locate candidate vertices
The second is the Adaptive Multi Vertex Finder, a global approach to vertex finding and fitting, which deploys the same adaptive vertex fitting technique as the Iterative Vertex Finder algorithm used in Run-2. This allows vertices to compete for nearby tracks in parallel, in order to take into account the vertex structure of the event.
This talk summarises the optimization and expected performance of the Adaptive Multi Vertex Finder algorithm and software, for conditions foreseen for Run-3 of the LHC. These studies are coupled to a newly optimised vertexing seeder algorithm and further performance studies in the ITk scenario.
|Consider for promotion||No|