Using the full Run-2 data recorded by the ATLAS detector, a search
for the elusive Higgs pair production decaying into four bottom quarks,
HH → bbbb, is presented in this thesis. The full Run-2 dataset corresponds to 126 fb−1
of integrated luminosity. The theoretical motivations
for this search, which are summarized in this thesis, are clear as the
search can probe the structure of the Higgs potential and Beyond the
Standard Model physics.
To reconstruct the HH → bbbb events a combination of multi-b-jet
triggers are used. Events are then selected if they contain at least four
small radius jets that have passed the b-tagging selection. These jets are
paired to reconstruct the Higgs candidates. As Monte Carlo simulations
cannot reliably reproduce the bbb¯b final state, a data-driven approach is
taken to produce the background estimate. This makes use of a neural
network to predict the background in the signal region. The data-driven
approach is validated by the use of several orthogonal control samples.
The search is used to set exclusion limits at a 95 % confidence level for
heavy resonances and non-resonant gluon-gluon fusion HH production.
Two benchmark signals consisting of a spin-0 narrow width scalar and a
spin-2 graviton were used for the resonant search. The upper limit on
the cross-section of the non-resonant Standard Model HH production
via gluon-gluon fusion was observed to be 5.1 times the Standard Model
prediction. The trilinear Higgs self-coupling was constrained to the range
of [-6.0, 15.0] times the Standard Model prediction. The improvements
made to the bbb¯b channel have made the search competitive with the
other final states. These optimizations will be useful to maximize the
potential of the HL-LHC program
