|M.Sc Student||Weiss Yaniv|
|Subject||Supersymmetry Signatures at the LHC|
|Department||Department of Physics||Supervisor||PROF. Yael Shadmi|
|Full Thesis text|
The aim of this thesis is to demonstrate the use of recently developed charm tagging techniques.
While still less efficient than the more mature b--tagging, application of machine learning is expected to improve present charm tagging efficiencies.
Charm tagging has already been used to increase sensitivity to the charm squarks and probe the Higgs--charm Yukawa.
We first review the standard model and motivate the existence of new physics beyond the SM.
Due to the small Yukawa couplings of the first two generations, it is conceivable that new physics production of second generation quarks is enhanced compared to the standard model, which is dominated by first generation quarks.
Thus, we propose a new variable, the charm fraction, to be used in collider searches for new physics.
We analyze the charm fraction in simplified supersymmetric models, with only the squarks, the gluino, and the bino present.
If the squark mass splittings are large they will be observable through meff and/or mT2 distributions.
We therefore assume that only the lightest mass--degenerate squarks can be produced at the high-luminosity LHC.
The charm fraction allows for a unique probe of new physics, complementing event counting and kinematic information.
It is particularly useful when the gluino is heavy, and thus squark--pair production is flavor blind.
Some supersymmetry breaking mechanisms allow for a large hierarchy between the gluino and squarks.
In contrast to event counting, the charm fraction can provide information on the underlying model, thereby helping to discriminate between different models.
With future improvements in charm tagging rates, measuring the charm fraction may yield information on the gluino mass, would be useful and even indicate whether the gluino is within reach of 100 TeV hadron collider.