Thesis Submitted to the Honors College at the University of Arizona (May, 2019)

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BACKGROUND CHARACTERIZATION IN THE 4TOP SEARCH AT THE ATLAS EXPERIMENT

Abstract

A data-driven approach is taken to estimate the background and find optimal cuts for the four-top-quark search at the ATLAS Experiment for √s = 13 TeV. Using 140fb^-1 of data generated from the Large Hadron Collider from 2015 through 2018, the Monte Carlo simulated background is reweighted by a function of H^T_all to match the distribution of data. This correction function is then used to build MC signal and background distributions. To find the best region to search for the four-top signal, the significance of the signal to background is measured for various lower bounds, and the optimal selection criteria of N_bjets >2 jets, N_jets > 9 jets, H^T_all > 660000 MeV, and jet_pt > 60000 MeV are chosen. These cuts produce a significance of 1.0077 and yield 60.22 expected signal events and 3511 expected background events in the data sample.