IRIS-HEP Fellow: Elliott Kauffman

Fellowship dates: May – Aug, 2022

Home Institution: Duke University

Project: Adapting PV-Finder to the CMS and ATLAS Experiments

PV-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)

Presentations and Publications
Current Status

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