Search for the four top quark process at the CMS experiment via the single lepton channel

Abstract

While the Standard Model (SM) of particle physics has been incredibly successful in describing fundamental particles and their interactions, there are a few phenomena that remain without explanation in the current understanding of the building blocks of this world. These open questions are the source of new ideas and motivation for searches for new physics with experiments at the Large Hadron Collider at CERN. One search that is very interesting, as it is sensitive to new physics that can expand the current SM to a complete theory, is the search for a physics process known as four top quark production. This thesis presents the search for four top quark production using data collected at CMS. The production of four top quarks is an incredibly rare process, yet to be observed, which has a large background originating from processes with similarly large jet multiplicity in their final states such as the production of a top quark and anti-top quark pair in association with extra jets from QCD radiation. The motivation for a study of the production of four top quarks at CMS is that its cross section may give indications of physics beyond the SM. The focus of this thesis is one of the possible decay channels, the single lepton channel (e or µ), which is one with a high probability of occurring, at around 26%. In this channel each top quark decays to produce a W boson and a bottom quark, where only one of the W bosons must decay to a lepton and an anti-neutrino. The final study of this PhD proposes a data-driven method for the estimation of backgrounds to tttt production in the single lepton channel that gives results of about the same magnitude but has different and fewer sources of uncertainty. In the future the data-driven method can also be applied to other decay channels. In addition, because the main limitation to this method is the statistical uncertainty from the input data, in the future with more data collected at CMS and minor adjustments to the method, the power of the search will increase.

Date of Award	9 May 2023
Original language	English
Awarding Institution	University of Bristol
Supervisor	Freya Blekman (Supervisor), Joel Goldstein (Supervisor) & Alberto Mariotti (Supervisor)