Axion searches in rare Higgs decays at ATLAS

The discovery of a Standard Model like Higgs boson was a major milestone for
the LHC. Despite this, the Standard Model (SM) and the underlying theories so
far are plagued by problems that arise both theoretically and experimentally. This
includes the Strong CP-problem, which is the theoretical argument that the SM
could break CP symmetry in strong interactions. However, no evidence of such
has been experimentally observed. The Higgs boson observation with a mass of
approximately 125 GeV does leave open the possibility for new particles which will
not violate the elementary gauge symmetries of the Standard Model and as such
creates the potential to search for these particles at low mass .
With this motivation my project will contribute to the searches of such particles.
The aim is to initiate the analysis for searching for a pseudo-scalar low mass particle
which we will call a, from the rare Higgs decay to Za. Particle a could identify
as a possible Axion-like particle (ALP) or Next-to-Minimal Supersymmetry Model
(NMSSM) candidate.
Axions and ALP's are theoretical particles resulting from the Peccei-Quinn
mechanism that describes a possible solution to the CP problem by introducing
a dynamic field to explain the CP-violating term, ALP's can couple to all SM
particles, however depending on their coupling and possible mass ranges searches
for ALP's differ significantly. Theoretical studies by Bauer (2017) show that there
are possible parameter regions present were LHC data could well be utilized to
search for ALPs in the decay channel H Za for masses in the range 0.1-10 GeV
and could be long lived In Higgs physics, ALP's could decay into a pair of
jets or photons alongside a Z-boson decaying into two leptons with a clean signal.
Previous searches for ALPs have been conducted at the LHC but have so far not
been successful.
A challenge with this study is the fact that R, the distance the ALP's photons
are from each other, is so small that during photon identification (ID) photons are
actually being misidentified. A major task of this project will focus on the analysis
of these photons by evaluating the substructure of the photon shower in the 1st
layer of the electromagnetic calorimeter (ECAL) to better distinguish those that
are misidentified and as such improve the overall analysis of this decay channel.
Machine learning approaches such as deep neural networks and other multivariate
analysis techniques, complemented by skills gained through working as part of the
Liverpool data intensive center for doctoral training (LIV.DAT), will be exhaustively
attempted for better photon reconstruction. By incrementally improving
issues related to the underlying analysis of this decay channel can pseudo-scalar
low mass particles and such be thoroughly investigated