IRIS-HEP Fellow: Omar Alterkait



Fellowship dates: Jan – Jun, 2021

Home Institution: University of Colorado, Boulder


Project: Offline Track Selection

The prospect of the HL-LHC and the high pileup associated with it has made track reconstruction much more challenging. Following track reconstruction, an offline algorithm that is able to distinguish real tracks (tracks associated with a single charged particle) from fake tracks (tracks not associated with a single charged particle) is beneficial. The CMS software contains a DNN for this task; however, this is based on the current detector. For the phase 2 upgrade of the CMS detector, the outer tracker is quite different which means that this task needs to be reevaluated. The goal of my project is to develop a more efficient post track reconstruction algorithm using deep learning to classify reconstructed tracks as either real or fake.

More information: My project proposal

Mentors:
  • Kevin Stenson (University of Colorado, Boulder)

Presentations

Current Status


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