This book explores the Higgs boson and its interactions with fermions, as well as the detector technologies used to measure it. The Standard Model of Particle Physics has been a groundbreaking theory in our understanding of the fundamental properties of the universe, but it is incomplete, and there are significant hints which require new physics. The discovery of the Higgs boson in 2012 was a substantial confirmation of the Standard Model, but many of its decay modes remain elusive. This book presents the latest search for Higgs boson decays into c-quarks using a proton-proton collision dataset collected by the ATLAS experiment at the Large Hadron Collider (LHC). This decay mode has yet to be observed and requires advanced machine learning algorithms to identify c-quarks in the experiment. The results provide an upper limit on the rate of Higgs boson decays to c-quarks and a direct measurement of the Higgs boson coupling strength to c-quarks. The book also discusses the future of particle physics and the need for significant improvements to the detector to cope with increased radiation damage and higher data rates at the High-Luminosity LHC. It presents the characterization of the ATLAS pixel detector readout chip for the inner detector upgrade (ITk). The chip was subjected to irradiations using X-rays and protons to simulate the radiation environment at the HL-LHC. The tests showed that all readout chip components, including the digital logic and analogue front-end, are sufficiently radiation-tolerant to withstand the expected radiation dose. Finally, this book describes monolithic pixel detectors as a possible technology for future pixel detectors. This book is ideal for individuals interested in exploring particle physics, the Higgs boson, and the development of silicon pixel detectors.

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.

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.

The work presented in this PhD dissertation is the first search at CMS for Higgs bosons produced in association with top quarks (ttH) in a final state consisting of only jets. The results presented in this book uncover a new class of ttH events that will help us elucidate our understanding of the Yukawa sector interactions between the Higgs boson and the top quark. Despite this being the most common decay signature for ttH, a large contamination of SM backgrounds makes it the most challenging for extracting a signal from data. The PhD thesis presents many sophisticated tools and techniques that were developed in order to overcome these challenges. These tools pave the way for future analyses to investigate other standard model and beyond-standard model physics.

This doctoral thesis focuses on the search for new phenomena in top-antitop quark (tt) final states with additional b-quark jets at the LHC. It uses the full Run 1 dataset collected by the ATLAS experiment in proton-proton collisions at √s=8 TeV. The final state of interest consists of an isolated lepton, a neutrino and at least six jets with at least four b-tagged jets, a challenging experimental signature owing to the large background from tt+heavy-flavor production. This final state is characteristic of ttH production, with the Higgs boson decaying into bb, a process that allows direct probing of the top-Higgs Yukawa coupling. This signature is also present in many extensions of the Standard Model that have been proposed as solutions to the hierarchy problem, such as supersymmetry or composite Higgs models, which predict the pair production of bosonic or fermionic top quark partners, or the anomalous production of four-top-quark events. All these physics processes have been searched for using an ambitious search strategy that has been developed on the basis of a combination of state-of-art theoretical predictions and a sophisticated statistical analysis to constrain in-situ the large background uncertainties. As a result, the most restrictive bounds to date on the above physics processes have been obtained.

The theoretical foundations of the Standard Model of elementary particles relies on the existence of the Higgs boson, a particle which has been revealed for the first time by the experiments run at the Large Hadron Collider (LHC) in 2012. As the Higgs boson is an unstable particle, its search strategies were based on its decay products. In this thesis, Francesco Pandolfi conducted a search for the Higgs boson in the H → ZZ → l + l - qq Decay Channel with 4.6 fb -1 of 7 TeV proton-proton collision data collected by the Compact Muon Solenoid (CMS) experiment. The presence of jets in the final state poses a series of challenges to the experimenter: both from a technical point of view, as jets are complex objects and necessitate of ad-hoc reconstruction techniques, and from an analytical one, as backgrounds with jets are copious at hadron colliders, therefore analyses must obtain high degrees of background rejection in order to achieve competitive sensitivity. This is accomplished by following two directives: the use of an angular likelihood discriminant, capable of discriminating events likely to originate from the decay of a scalar boson from non-resonant backgrounds, and by using jet parton flavor tagging, selecting jets compatible with quark hadronization and discarding jets more likely to be initiated by gluons. The events passing the selection requirements in 4.6 fb -1 of data collected by the CMS detector are examined, in the search of a possible signal compatible with the decay of a heavy Higgs boson. The thesis describes the statistical tools and the results of this analysis. This work is a paradigm for studies of the Higgs boson with final states with jets. The non-expert physicists will enjoy a complete and eminently readable description of a proton-proton collider analysis. At the same time, the expert reader will learn the details of the searches done with jets at CMS.

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