Search for the $H\rightarrow b \bar{b}$ Decay of the Standard Model Higgs Boson in Associated Production with Vector Bosons Using ATLAS Data at $\sqrt{s}$ = 8 TeV

In this thesis, a search for the $H \rightarrow b \bar{b}$ decay of the Standard-Model Higgs boson is presented. A dataset of $20.2\, \mathrm{fb}^{-1}$ recorded by the ATLAS detector at CERN is searched for events, where Higgs bosons are produced in association with a vector boson that decays to charged leptons at a centre-of-mass energy of $\sqrt{s} = 8\, \mathrm{TeV}$. Machine learning with boosted decision trees is used to implement the most sensitive $VH \rightarrow Vb \bar{b}$ search on $\sqrt{s} = 8\, \mathrm{TeV}$ LHC data with charged leptons, the ATLAS search published in 2015. It is further shown that the machine-learning part of this search can be improved by training boosted decision trees with Lorentz-invariant observables, which increases the sensitivity by 10 %, and reduces systematic uncertainties by 16 %. For a Higgs boson of $m_H = 125\, \mathrm{GeV}$, a local excess over the background prediction at 99.2 % confidence level is observed, which corresponds to a discovery significance of $2.4\,\sigma$, whereas $1.9\,\sigma$ were expected from simulations. The ratio of the observed signal strength compared to the Standard-Model prediction is $\mu=1.3^{+0.7}_{-0.6}$.