The discovery in 2012 of the Higgs boson at the Large Hadron Collider (LHC) represents a milestone for the Standard Model (SM) of particle physics. Most of the SM Higgs production and decay rates have been measured at the LHC with increased precision. However, despite its experimental success, the SM is known to be only an effective manifestation of a more fundamental description of nature. The scientific research at the LHC is strongly focused on extending the SM by searching, directly or indirectly, for indications of New Physics. The extensive physics program requires increasingly advanced computational and algorithmic techniques. In the last decades, Machine Learning (ML) methods have made a prominent appearance in the field of particle physics, and promise to address many challenges faced by the LHC. This thesis presents the analysis that led to the observation of the SM Higgs boson decay into pairs of bottom quarks. The analysis exploits the production of a Higgs boson associated with a vector boson whose signatures enable efficient triggering and powerful background reduction. The main strategy to maximise the signal sensitivity is based on a multivariate approach. The analysis is performed on a dataset corresponding to a luminosity of 79.8/fb collected by the ATLAS experiment during Run-2 at a centre-of-mass energy of 13 TeV. An excess of events over the expected background is found with an observed (expected) significance of 4.9 (4.3) standard deviation. A combination with results from other \Hbb searches provides an observed (expected) significance of 5.4 (5.5). The corresponding ratio between the signal yield and the SM expectation is 1.01 +- 0.12 (stat.)+ 0.16-0.15(syst.). The 'observation' analysis was further extended to provide a finer interpretation of the V H(H → bb) signal measurement. The cross sections for the VH production times the H → bb branching ratio have been measured in exclusive regions of phase space. These measurements are used to search for possible deviations from the SM with an effective field theory approach, based on anomalous couplings of the Higgs boson. The results of the cross-section measurements, as well as the constraining of the operators that affect the couplings of the Higgs boson to the vector boson and the bottom quarks, have been documented and discussed in this thesis. This thesis also describes a novel technique for the fast simulation of the forward calorimeter response, based on similarity search methods. Such techniques constitute a branch of ML and include clustering and indexing methods that enable quick and efficient searches for vectors similar to each other. The new simulation approach provides optimal results in terms of detector resolution response and reduces the computational requirements of a standard particles simulation.

This thesis reports on the search for dark matter in data taken with the ATLAS detector at CERN’s Large Hadron Collider (LHC). The identification of dark matter and the determination of its properties are among the highest priorities in elementary particle physics and cosmology. The most likely candidate, a weakly interacting massive particle, could be produced in the high energy proton-proton collisions at the LHC. The analysis presented here is unique in looking for dark matter produced together with a Higgs boson that decays into its dominant decay mode, a pair of b quarks. If dark matter were seen in this mode, we would learn directly about the production mechanism because of the presence of the Higgs boson. This thesis develops the search technique and presents the most stringent production limit to date.

The analysis described in this thesis is the search for the Higgs boson, decaying into bb pair, in the associated production with a vector boson, in the extreme Higgs boson transverse momentum region where the Higgs boson is reconstructed using the large-R jet technique. The use of the large-R jets allows to add a part of the phase space unexplored so far, which is particularly sensitive to possible new physics. The analysed data have been collected at LHC by the ATLAS detector between 2015 and 2018 at a centre-of-mass energy of √s = 13 TeV. The same dataset has been used to perform the differential pp → ZH and pp → WH cross-section measurements used to extract the information on the Higgs couplings and to put limits on Beyond the Standard Model effects. Furthermore the analysis has been re-used to perform a cross-section measurement of the diboson ZZ and WZ processes because the diboson and the Higgs processes have a similar topology. For the first time the ZZ(bb) and WZ(bb) cross-sections are measured at √s = 13 TeV and the observed cross-section measurements are consistent with the Standard Model predictions.

This PhD thesis documents two of the highest-profile searches for supersymmetry performed at the ATLAS experiment using up to 80/fb of proton-proton collision data at a center-of-mass energy of 13 TeV delivered by the Large Hadron Collider (LHC) during its Run 2 (2015-2018). The signals of interest feature a high multiplicity of jets originating from the hadronisation of b-quarks and large missing transverse momentum, which constitutes one of the most promising final state signatures for discovery of new phenomena at the LHC. The first search is focused on the strong production of a pair of gluinos, with each gluino decaying into a neutralino and a top-antitop-quark pair or a bottom-antibottom-quark pair. The second search targets the pair production of higgsinos, with each higgsino decaying into a gravitino and a Higgs boson, which in turn is required to decay into a bottom-antibottom-quark pair. Both searches employ state-of-the-art experimental techniques and analysis strategies at the LHC, resulting in some of the most restrictive bounds available to date on the masses of the gluino,neutralino, and higgsino in the context of the models explored.

This book reports on the search for a new heavy particle, the Vector-Like Top quark (VLT), in the Large Hadron Collider (LHC) at CERN. The signal process is the pair production of VLT decaying into a Higgs boson and top quark (TT→Ht+X, X=Ht, Wb, Zt). The signal events result in top–antitop quarks final states with additional heavy flavour jets. The book summarises the analysis of the data collected with the ATLAS detector in 2015 and 2016. In order to better differentiate between signals and backgrounds, exclusive taggers of top quark and Higgs boson were developed and optimised for VLT signals. These efforts improved the sensitivity by roughly 30%, compared to the previous analysis. The analysis outcomes yield the strongest constraints on parameter space in various BSM theoretical models. In addition, the book addresses detector operation and the evaluation of tracking performance. These efforts are essential to properly collecting dense events and improving the accuracy of the reconstructed objects that are used for particle identification. As such, they represent a valuable contribution to data analysis in extremely dense environments.

In this work, the interaction between the Higgs boson and the top quark is studied with the proton-proton collisions at 13 TeV provided by the LHC at the CMS detector at CERN (Geneva). At the LHC, these particles are produced simultaneously via the associate production of the Higgs boson with one top quark (tH process) or two top quarks (ttH process). Compared to many other possible outcomes of the proton-proton interactions, these processes are very rare, as the top quark and the Higgs boson are the heaviest elementary particles known. Hence, identifying them constitutes a significant experimental challenge. A high particle selection efficiency in the CMS detector is therefore crucial. At the core of this selection stands the Level-1 (L1) trigger system, a system that filters collision events to retain only those with potential interest for physics analysis. The selection of hadronically decaying τ leptons, expected from the Higgs boson decays, is especially demanding due to the large background arising from the QCD interactions. The first part of this thesis presents the optimization of the L1 τ algorithm in Run 2 (2016-2018) and Run 3 (2022-2024) of the LHC. It includes the development of a novel trigger concept for the High-Luminosity LHC, foreseen to start in 2027 and to deliver 5 times the current instantaneous luminosity. To this end, sophisticated algorithms based on machine learning approaches are used, facilitated by the increasingly modern technology and powerful computation of the trigger system. The second part of the work presents the search of the tH and ttH processes with the subsequent decays of the Higgs boson to pairs of τ lepton, W bosons or Z bosons, making use of the data recorded during Run 2. The presence of multiple particles in the final state, along with the low cross section of the processes, makes the search an ideal use case for multivariant discriminants that enhance the selectivity of the signals and reject the overwhelming background contributions. The discriminants presented are built using state-of-the-art machine learning techniques, able to capture the correlations amongst the processes involved, as well as the so-called Matrix Element Method (MEM), which combines the theoretical description of the processes with the detector resolution effects. The level of sophistication of the methods used, along with the unprecedented amount of collision data analyzed, result in the most stringent measurements of the tH and ttH cross sections up to date.

Precision measurements of the Higgs boson’s properties are a powerful tool to look for deviations from the predictions of the Standard Model (SM) of particle physics. The 139/fb of proton-proton collision data which have been collected by the ATLAS experiment during Run 2 of the LHC, offer an opportunity to investigate rare Higgs-boson topologies, which are particularly sensitive to new physics scenarios but experimentally difficult to access. Several such measurements, which target Higgs-boson decays to heavy-flavour quarks, as well as their combinations are presented in this thesis. A novel analysis that measures Higgs-boson production in association with a heavy vector boson V (VH, with V=W,Z) at high energies is presented. Dedicated Higgs-boson reconstruction techniques are applied to reconstruct the highly Lorentz-boosted Higgs-boson decays into pairs of bottom quarks. The measurement is subsequently combined with a VH cross-section measurement at low and intermediate pT(V) to provide a differential cross-section measurement in kinematic fiducial volumes over the largest possible pT(V) range. All cross-section measurements agree with the SM predictions within relative uncertainties that range from 30% to 300%. The results are furthermore interpreted as limits on the parameters of a SM effective field theory. Finally, a combination of measurements of Higgs decays to heavy-flavour quarks is used to experimentally determine that the Higgs-boson coupling to charm quarks is weaker than to bottom quarks, as predicted by the SM. The target audience for the thesis are physicists and physics students, in particular those with a background in high energy physics.