Wing Sheung Chan

2 Introduction is purely based on empirical evidence and simplicity of the model, but lacks fundamental motivations. Therefore, if observed, lepton flavour violation would be an unequivocal evidence of BSM physics, and could point us in the right direction in identifying possible “loopholes” in the SM. In particular, the decay of a Z boson into an electron or muon and a τ lepton ( Z → `τ ) is an interesting signal of lepton flavour violation. Searches for Z → `τ decays have been performed using data collected from the Large Electron-Positron Collider (LEP), and stringent limits on the probability of such decays have been set. However, new opportunities have opened up as the Large Hadron Collider (LHC) and the ATLAS detector are collecting more and more data, allowing the search for Z → `τ decays to reach an unprecedented sensitivity. Currently, with the data collected by the ATLAS detector and through careful analysis, we are able to surpass the sensitivity of the LEP experiments for the first time after more than two decades since the last Z → `τ search result from the LEP experiments was published. This marks the beginning of a new era for lepton flavour violation searches. This thesis is a documentation of this exciting work. The thesis is divided into six chapters: Chapter 1 gives a brief introduction to the Standard Model, with a focus on parts that are most relevant to this thesis. An introduction to a handful of selected BSM theories related to lepton flavour violation is also given, followed by a summary of the current experimental status of lepton flavour violation searches. At last, we discuss the motivation for the chosen search channel, Z → `τ . Chapter 2 provides an overview of the LHC and the ATLAS detector. Chapter 3 outlines the algorithms used to reconstruct and identify physics objects from the data collected by the ATLAS detector. A focus is given to the reconstruction and identification of hadronic τ decays, which are especially important to the presented analysis, and are work to which the author has made important contributions. Chapter 4 describes how observed and simulated proton–proton collision events are selected and classified in the search for Z → `τ decays. It also documents the training and usage of neural network classifiers for signal and background classification. Chapter 5 details the methods that are used to model the signal and background events, which generate predictions that can be compared with observations from data. Chapter 6 presents the statistical analysis method and the final results of the analysis. These are followed by a conclusion and outlook. The analysis described in Chapters 4– 6 is the author’s own, original work. The results have also been published as Reference [1] .