Search for the Higgs boson produced in association with a vector boson and decaying into a pair of b-quarks using large-R jets with the ATLAS detector

After the Higgs discovery at LHC in 2012, most of ATLAS analyses are focusing on precise measurements of Higgs kinematic properties and on the search of new decay modes sensitive to physics Beyond the Standard Model (BSM). Among all the processes, the Higgs boson decay to b-quarks is particularly interesting, thanks to its branching ratio of about 58% in the Standard Model (SM). The observation of this decay at the LHC has been obtained only recently, after seven years from the Higgs boson discovery, because this channel is affected by large backgrounds arising from multi-jet production that make a real challenge to trigger and extract the signal. The best sensitivity is presently obtained by studying the associated Higgs boson production with a vector boson (Z or W) decaying leptonically. The analysis described in this thesis is the search of 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 $\sqrt{s}$ = 13 TeV. The same dataset has been used to perform the differential pp $\to$ ZH and pp $\to$ WH cross-section measurements used to extract the information on the Higgs couplings and to put limits on BSM effects. Furthermore, the analysis has been re-used to perform cross-section measurements 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 have been measured at $\sqrt{s}$= 13 TeV and the observed cross-section measurements are consistent with the Standard Model predictions.