Triggering and Reconstructing Hadronic Jets in the Search for Dark Matter and Supersymmetry with the ATLAS Experiment

Precision tests of the Standard Model of Particle Physics and searches for phenomena beyond the Standard Model are the focus for the ATLAS experiment at the Large Hadron Collider (LHC) over the next decade. The beginning of Run 3 of the LHC in 2022 and the eventual commissioning of the detector for High Luminosity operations with an upgraded LHC from 2029 provides a unique opportunity to extend the coverage of Beyond the Standard Model searches to new and hard to reach particle properties (parameter space). Many signatures of both Standard Model and Beyond the Standard Model physics involve the production of hadronic jets, sprays of composite particles called hadrons. Low-mass searches for new particles using hadronic jets are limited by extremely high-rate background processes - there are significant limitations on the amount of LHC data that can be saved for analysis. The application of novel techniques for data acquisition and selection (triggering) plays an important role in collecting datasets with sufficient statistical power and high sensitivity to the production of low-mass particles. This thesis describes studies of different triggers that could be used in Run 3 searches for multi-jet resonances from supersymmetric particles in the mass range between 100 GeV and 400 GeV. Additional discussions of early studies to project the sensitivity of these analyses in the conditions of the High-Luminosity LHC (HL-LHC) are also included. In the high-mass and high-momentum region of parameter space the decay products of hypothetical particles can be highly collimated and reconstructed within a single large jet (a "cone" around the decay products). The identification of the "parent particle" of these jets is an important aspect of selecting data to analyse. The jet identification (tagging) focus of this thesis consists of the development of top quark identification algorithms for use in HL-LHC simulations. Basic tagging algorithms are developed and compared to more complex Run 2 taggers to provide a first set of recommendations for identifying hadronic top quark decays in HL-LHC simulations.