2026-09-22T18:59:44Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/130095 2026-02-10 col_2142_5131 col_2142_8859 com_2142_5130 com_2142_8858 com_2142_234

application/pdf en text Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2027-08-01 The student, Cunwei Fan, accepted the attached license on 2025-07-10 at 19:55. The student, Cunwei Fan, submitted this Dissertation for approval on 2025-07-10 at 20:03. This Dissertation was approved for publication on 2025-07-14 at 13:39. DSpace SAF Submission Ingestion Package generated from Vireo submission #22495 on 2025-10-25 at 15:30:58 Searches for supersymmetric particles in leptonic final states with the ATLAS detector Fan, Cunwei 2025-07-14 Hooberman, Benjamin H. El-Khadra, Aida Cooper, Lance Noronha, Jorge Long-lived Particle Atlas Hough Transfrom Susy eng 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. 2025-08 Text https://hdl.handle.net/2142/130095 Copyright 2025 Cunwei Fan Physics Physics University of Illinois Urbana-Champaign Ph.D. Dissertation