Graph Neural Network Flavour Tagging and Boosted Higgs Measurements at the LHC

This thesis presents investigations into the challenges of, and potential improvements to, $b$-jet identification ($b$-tagging) at the ATLAS experiment at the Large Hadron Collider (LHC). The presence of $b$-jets is a key signature of many interesting physics processes such as the production of Higgs bosons, which preferentially decay to a pair of $b$-quarks. In this thesis, a particular focus is placed on the high transverse momentum regime, which is a critical region in which to study the Higgs boson and the wider Standard Model, but also a region within which $b$-tagging becomes increasingly difficult. As $b$-tagging relies on the accurate reconstruction of charged particle trajectories (tracks), the tracking performance is investigated and potential improvements are assessed. Track reconstruction becomes increasingly difficult at high transverse momentum due to the increased multiplicity and collimation of tracks, and also due to the presence of displaced tracks from the decay of a long-flying $b$-hadron. The investigations reveal that the quality selections applied during track reconstruction are suboptimal for $b$-hadron decay tracks inside high transverse momentum $b$-jets, motivating future studies into the optimisation of these selections. Two novel approaches are developed to improve $b$-tagging performance. Firstly, an algorithm which is able to classify the origin of tracks is used to select a more optimal set of tracks for input to the $b$-tagging algorithms. Secondly, a graph neural network (GNN) jet flavour tagging algorithm has been developed. This algorithm directly accepts jets and tracks as inputs, making a break from previous algorithms which relied on the outputs of intermediate taggers. The model is trained to simultaneously predict the jet flavour, track origins, and the spatial track-pair compatibility, and demonstrates marked improvements in $b$-tagging performance both at low and high transverse momenta. The closely related task of $c$-jet identification also benefits from this approach. Analysis of high transverse momentum $H\rightarrow bb$ decays, where the Higgs boson is produced in association with a vector boson, was performed using 139 ${\text{fb}^{-1}}$ of 13 TeV proton-proton collision data from Run 2 of the LHC. This analysis provided first measurements of the $VH, H\rightarrow bb$ process in two high transverse momentum regions, and is described with a particular focus on the background modelling studies performed by the author.