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TY - THES AU - Engelke, Frederic TI - Searches for supersymmetric dark matter in semileptonic final states at the CMS experiment employing angular correlation and deep learning techniques followed by a reinterpretation in the pMSSM19 framework PB - RWTH Aachen University VL - Dissertation CY - Aachen M1 - RWTH-2025-05419 SP - 1 Online-Ressource : Illustrationen PY - 2025 N1 - Veröffentlicht auf dem Publikationsserver der RWTH Aachen University N1 - Dissertation, RWTH Aachen University, 2025 AB - The nature of dark matter (DM) remains one of the most compelling mysteries in modern physics. Despite DM exceeding the visible (baryonic) matter by a factor of four, its origin and properties are yet to be understood. This thesis explores the dark matter problem through the framework of supersymmetry (SUSY), a theoretical extension of the Standard Model of particle physics. Using data collected during the Large Hadron Collider (LHC) Run 2 (2016-2018) by the Compact Muon Solenoid (CMS) experiment, with an integrated luminosity of L = 138 \textfb<sup>−1</sup>, multiple analysis strategies are employed to search for signatures of SUSY particles that present viable DM candidates. The first analysis utilizes a cut-and-count approach targeting the m<sub>~g</sub>-m<sub>~χ<sub>0</sub><sup>1</sup></sub> mass plane via angular correlation between selected physics objects, combined with a data-driven method to address limitations in background modeling via transfer factors and corrections. This analysis achieved exclusion limits for gluino masses up to 2050 GeV and neutralino masses up to 1070 GeV. Subsequently, these results were reinterpreted within the phenomenological MSSM framework (pMSSM19), constraining additional SUSY parameters and highlighting potential regions of interest based on observed data excesses. To further enhance the sensitivity, a machine learning-based approach was developed, utilizing a deep neural network (DNN) to classify collision events and define signal regions based on DNN scores. This novel methodology expands the exclusion limits up to 1450 GeV for m<sub>~χ<sub>0</sub><sup>1</sup></sub> and up to 2230 GeV for m<sub>~g</sub> and demonstrates the advantages of sophisticated computational techniques in modern collider analyses. Also, the HO, the outer hadron calorimeter of the CMS detector, was evaluated as a potential trigger system for long-lived particle (LLP) detection, addressing challenges in identifying signatures predicted by SUSY theories. LB - PUB:(DE-HGF)11 DO - DOI:10.18154/RWTH-2025-05419 UR - https://publications.rwth-aachen.de/record/1013266 ER -