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.

In 1964, a mechanism explaining the origin of particle masses was proposed by Robert Brout, François Englert, and Peter W. Higgs. 48 years later, in 2012, the so-called Higgs boson was discovered in proton-proton collisions recorded by experiments at the LHC. Since then, its ability to interact with quarks remained experimentally unconfirmed. This book presents a search for Higgs bosons produced in association with top quarks tt̄H in data recorded with the CMS detector in 2016. It focuses on Higgs boson decays into bottom quarks H → bb̅ and top quark pair decays involving at least one lepton. In this analysis, a multiclass classification approach using deep learning techniques was applied for the first time. In light of the dominant background contribution from tt̄ production, the developed method proved to achieve superior sensitivity with respect to existing techniques. In combination with searches in different decay channels, the presented work contributed to the first observations of tt̄H production and H → bb̅ decays.

This Thesis describes the first measurement of, and constraints on, Higgs boson production in the vector boson fusion mode, where the Higgs decays to b quarks (the most common decay channel), at the LHC. The vector boson fusion mode, in which the Higgs is produced simultaneously with a pair of quark jets, provides an unparalleled opportunity to study the detailed properties of the Higgs, including the possibility of parity and CP violation, as well as its couplings and mass. It thus opens up this new field of study for precision investigation as the LHC increases in energy and intensity, leading the way to this new and exciting arena of precision Higgs research.

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 book describes the searches that lead to the discovery of a Higgs boson performed at CMS, one of the two main experiments at the CERN LHC. After an overview of the theory and of the CMS experiment, all search channels are described, with emphasis on the ones with the best sensitivity. The statistical methodology used to analyse and the outcomes of the searches and the discovery results are then presented in detail.

The proceedings of the July 1989 Workshop contribute to the ongoing scientific debate on the best strategies of discovering the Higgs boson (and top quark). The papers are organized in five parts, covering theoretical issues, searches for light scalars, Higgs searches in hadronic collisions, Higgs searches in e +e -annihilation, and present experim