We present a search for standard model Higgs boson production in association with a W boson in proton-antiproton collisions (p{bar p} → W{sup {+-}}H → l[nu]b{bar b}) at a center of mass energy of 1.96 TeV. The search employs data collected with the CDF II detector that correspond to an integrated luminosity of approximately 1.9 fb−1. We select events consistent with a signature of a single charged lepton (e{sup {+-}}/[mu]{sup {+-}}), missing transverse energy, and two jets. Jets corresponding to bottom quarks are identified with a secondary vertex tagging method, a jet probability tagging method, and a neural network filter. We use kinematic information in an artificial neural network to improve discrimination between signal and background compared to previous analyses. The observed number of events and the neural network output distributions are consistent with the standard model background expectations, and we set 95% confidence level upper limits on the production cross section times branching fraction ranging from 1.2 to 1.1 pb or 7.5 to 102 times the standard model expectation for Higgs boson masses from 110 to 150 GeV/c2, respectively.

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.

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.

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.

We present a search for the standard model Higgs boson production in association with a $W$ boson in proton-antiproton collisions ($p\bar{p}\rightarrow W\̂pm H \rightarrow \ell\nu b\bar{b}$) at a center of mass energy of 1.96 TeV. The search employs data collected with the CDF II detector which correspond to an integrated luminosity of approximately 2.7 fb${̂-1}$. We recorded this data with two kinds of triggers. The first kind required high-p$_T$ charged leptons and the second required both missing transverse energy and jets. The search selects events consistent with a signature of a single lepton ($e\̂pm/\mu\̂pm$), missing transverse energy, and two jets. Jets corresponding to bottom quarks are identified with a secondary vertex tagging method and a jet probability tagging method. Kinematic information is fed in an artificial neural network to improve discrimination between signal and background. The search finds that both the observed number of events and the neural network output distributions are consistent with the standard model background expectations, and sets 95% confidence level upper limits on the production cross section times branching ratio. The limits are expressed as a ratio to the standard model production rate. The limits range from 3.6 (4.3 expected) to 61.1 (43.2 expected) for Higgs masses from 100 to 150 GeV/$c{̂2}$, respectively.