IRIS-HEP Fellow: Elliott Kauffman
Fellowship dates: May – Aug, 2022
Home Institution: Duke University
Project: Adapting PV-Finder to the CMS and ATLAS ExperimentsPV-Finder is a hybrid deep learning algorithm which identifies primary vertices. This algorithm was developed for use in conjunction with the LHCb detector in Run 3 of the LHC, which will experience a luminosity that is 5.5 times that of Run 2. In LHCb data, the efficiency of the CNN has inreased from to 90% to past 98% over the course of the past few years. The success of PV-Finder motivates its extension to both the ATLAS and CMS experiments. This project is concerned with the adaptation of the PV-Finder algorithm to ATLAS and CMS. Difference in detector geometry, data structure, density of particle tracks, and track resolution between experiments generate enough variation to motivate a dedicated project.
More information: My project proposal
Henry Schreiner (Princeton University)
Mike Sokoloff (University of Cincinnati)
Rocky Bala Garg (Standord University)