ATLAS

Abstract:

The ATLAS EventIndex system comprises the catalogue of all events collected, processed or generated by the ATLAS experiment at the CERN LHC accelerator, and all associated software tools to collect, store and query this information. ATLAS records several billion particle interactions every year of operation, processes them for analysis and generates even larger simulated data samples; a global catalogue is needed to keep track of the location of each event record and be able to search and retrieve specific events for in-depth investigations. Each EventIndex record includes summary information on the event itself and the pointers to the files containing the full event. Most components of the EventIndex system are implemented using BigData free and open-source software. This paper describes the architectural choices and their evolution in time, as well as the past, current and foreseen future implementations of all EventIndex components.

Abstract:

The limitations of the Standard Model (SM) of particle physics have perplexed physicists for many years, prompting the exploration of various theoretical SM extensions. This thesis utilises data from the ATLAS experiment, obtained through proton-proton collisions with an integrated luminosity of 139 fb^{−1} at a centre-of-mass energy of 13 TeV, to search for particles predicted by these theories. Searches for Z' bosons and leptoquarks (LQ) are conducted by employing analysis techniques developed during the 2020 ATLAS search for heavy neutral Higgs boson (H/A/h) decays to two tau leptons, as predicted by the Minimal Supersymmetric Standard Model (MSSM). In addition, this thesis presents preliminary work on enhancing the 2020 MSSM H/A/h → τ^{+} τ^{−} analysis using machine learning techniques and other optimisations. Finally, the progress made by the University of Sheffield towards the mass production of strip barrel modules for the forthcoming ATLAS Inner Tracker upgrade is discussed. No significant deviations from the predictions of the SM are observed in any of the searches. Consequently, upper limits at 95% confidence level are established for various parameters, and the observed limits are utilised to exclude mass ranges for specific models. The Sequential Standard Model (SSM) is used to define the Z' particle in this thesis, and the search results contribute to the ATLAS combination effort investigating the Heavy Vector Triplet (HVT) model. For the SSM, Z' masses below 3.06 TeV are excluded. Additional constraints are provided on the HVT model, for the fermion-Higgs {g_{f} , g_{H}} and generation-inclusive (third-generation) quark-lepton {g_{q} , g_{l}} ({g_{q3} , g_{l3}}) coupling parameter planes, assuming fermion universality and the Model A benchmark scenario (g_H = −0.56), respectively. In the LQ analysis, masses below 1.28 TeV (1.35 TeV) are excluded for the \tilde{S̃}_{1} (U_{1}) models. By employing the machine learning and optimisation techniques to enhance the 2020 results, up to 4.2 (2.6) times improvement in the cross-section × branching ratio upper limit as a function of signal mass is demonstrated for the b-associated (gluon-gluon fusion) production modes. Improvements of up to 3.1 (2.9) in the tan β upper limit as a function of m_{A} are shown for the hMSSM (M_{h}^{125}) benchmark scenarios. The improvements for the MSSM occur exclusively at lower mass points