University of Illinois Urbana-Champaign

Searches for supersymmetric particles in leptonic final states with the ATLAS detector

Fan, Cunwei

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https://hdl.handle.net/2142/130095

Description

Title
Searches for supersymmetric particles in leptonic final states with the ATLAS detector
Author(s)
Fan, Cunwei
Issue Date
2025-07-14
Director of Research (if dissertation) or Advisor (if thesis)
Hooberman, Benjamin
Doctoral Committee Chair(s)
El-Khadra, Aida
Committee Member(s)
  • Cooper, Lance
  • Noronha, Jorge
Department of Study
Physics
Discipline
Physics
Degree Granting Institution
University of Illinois Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
  • Long-lived particle
  • ATLAS
  • Hough Transfrom
  • SUSY
Abstract
This thesis presents a search for displaced leptons, a characteristic signature of long-lived particles (LLPs), using data collected by the ATLAS detector at the LHC. The analysis targets leptonic final states in proton--proton collisions from Run~2 and early Run~3, leveraging newly developed LRT-based triggers and a data-driven background estimation strategy. No significant excess over the Standard Model background is observed, and exclusion limits are set on signal model parameters such as slepton mass, lifetime for two representative supersymmetric (SUSY) scenarios. Beyond the search itself, this thesis contributes to the broader experimental toolkit for LLP detection. To enable real-time identification of displaced tracks at the High-Luminosity LHC, a Hough Transform-based algorithm is implemented on an FPGA, providing fast online pattern recognition capabilities for track triggering. Additionally, a GRU-based recurrent neural network is developed to improve prompt lepton identification, particularly at low transverse momentum, surpassing traditional cut-based methods. Together, these efforts enhance the ATLAS experiment’s sensitivity to long-lived particles and provide essential algorithmic tools for future LLP searches across a range of theoretical models.
Graduation Semester
2025-08
Type of Resource
Thesis
Handle URL
https://hdl.handle.net/2142/130095
Copyright and License Information
Copyright 2025 Cunwei Fan

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