Meirin in Meyrin: machine learning in the t t¯z 2f channel and preparing ATLAS data for education worldwide

Run 2 of the Large Hadron Collider at CERN provided proton–proton collisions at a centre-of-mass energy of 13 TeV from 2015 to 2018. The ATLAS experiment is one of the experiments recording proton–proton collisions at the Large Hadron Collider, having recorded 139.0 fb-1of data in Run 2. Analysis of this dataset has provided an unprecedented arena to undertake precision measurements of the top quark, the heaviest fundamental particle discovered to date. Indeed, the Large Hadron Collider is sometimes called a “top quark factory". The interaction between top quarks and Z bosons provides a precise probe of the electroweak force, by studying the associated production of a Z with a top-antitop quark pair (tt¯Z) at the LHC. This thesis focuses on the 2-Lepton-Opposite-Sign channel of the tt¯Z process, which is being analysed for the first time with the full Run 2 dataset. By studying the 2-Lepton-Opposite-Sign channel, it is possible to reconstruct properties of the Z boson directly, due to sensitive lepton identification and kinematic measurement by the ATLAS detector. Therefore, this channel provides efficient Z boson reconstruction in studying the tt¯Z process. Multivariate analyses have been developed for this thesis to select tt¯Z 2-Lepton-Opposite-Sign events within Run 2 LHC data. The multivariate analyses included variables regarding leptons, jets and missing transverse momentum in the final state. Z bosons were reconstructed in selected tt¯Z 2-Lepton-Opposite-Sign events, providing additional variables for multivariate analyses. Including the 2-Lepton-Opposite-Sign channel in the overall cross-section measurement of the tt¯Z process provided a more sensitive cross-section measurement using the full Run 2 ATLAS dataset, due to the extra statistics compared to the 3-Lepton and 4-Lepton channels alone. In addition to the multivariate analyses developed for the ATLAS measurement of the tt¯Z process, similar multivariate analyses were developed using ATLAS Open Data; proton–proton collision data collected by ATLAS, processed and made available to the public. The purpose of developing multivariate analyses with ATLAS Open Data was to create, test and demonstrate educational uses of particle-physics data. Experimental and simulated data for the tt¯Z process, the code to perform multivariate analyses, various educational resources and extensive documentation are now publicly available for students around the world to analyse and learn for themselves.