Undergraduate Honors Thesis


Offline Track Selection at the CMS Detector Public Deposited

  • The Standard Model has made incredible predictions in particle physics. The Large Hadron Collider (LHC) is colliding protons to probe new physics beyond the standard model. These collisions occur through bunches of protons that cross inside detectors at a rate of 40 MHz. Multiple pairs of protons collide in each bunch, which is called pileup. As protons collide, many particles are produced, leaving behind tracks as they move through the detector. After a series of upgrades occurring in the next six years, the pileup is expected to increase from 50 to 200. The track reconstruction algorithm increases non-linearly in complexity with pileup. With larger pileup, the number of fake tracks (tracks not associated with any particle) increases. My research aims to use Machine Learning to create a model capable of differentiating real vs. fake tracks after they come out of the algorithm.

Date Awarded
  • 2021-04-06
Academic Affiliation
Committee Member
Granting Institution
Last Modified
  • 2021-05-13
Resource Type
Rights Statement


In Collection: