alexstoken / ttbar_bkg

UArizona Honors Thesis project: ttbar background estimation analysis for the ATLAS experiment. Tucson, AZ

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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 HTall 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 Nbjets >2 jets, Njets > 9 jets, HTall > 660000 MeV, and jetpt > 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.

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UArizona Honors Thesis project: ttbar background estimation analysis for the ATLAS experiment. Tucson, AZ


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