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This thesis presents a search for long-lived particles decaying into displaced electrons and/or muons with large impact parameters. This signature provides unique sensitivity to the production of theoretical lepton-partners, sleptons. These particles are a feature of supersymmetric theories, which seek to address unanswered questions in nature. The signature searched for in this thesis is difficult to identify, and in fact, this is the first time it has been probed at the Large Hadron Collider (LHC). It covers a long-standing gap in coverage of possible new physics signatures. This thesis describes the special reconstruction and identification algorithms used to select leptons with large impact parameters and the details of the background estimation. The results are consistent with background, so limits on slepton masses and lifetimes in this model are calculated at 95% CL, drastically improving on the previous best limits from the Large Electron Positron Collider (LEP).

A search for neutral Higgs bosons decaying into tau pairs is presented using data in p$\bar{p}$ collisions at √s = 1.96 TeV. One of the tau leptons is identified via its decay into an electron or muon and the other via its decay into a hadronic final state. The data, corresponding to an integrated luminosity of around 1.0 fb-1, were collected with the D0 detector at the Fermilab Tevatron collider between April 2002 and February 2006. No significant excess of events above the background expectation is observed and limits on the cross section times branching ratio for neutral Higgs bosons decaying into tau pairs, p$\bar{p}$ → [Phi] → [tau]+[tau]-, are set. The cross section limits are interpreted as exclusions in the parameter space of the minimal supersymmetric Standard Model, resulting in exclusions in the range 40

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.

The book gives a quite complete and up-to-date picture of the Standard Theory with an historical perspective, with a collection of articles written by some of the protagonists of present particle physics. The theoretical developments are described together with the most up-to-date experimental tests, including the discovery of the Higgs Boson and the measurement of its mass as well as the most precise measurements of the top mass, giving the reader a complete description of our present understanding of particle physics.