Optimized Top Quark Analysis with the Decision Tree

Abstract

We present an optimized and physically motivated method for separating top quark signal events from background events at the Tevatron. For the top quark signal $t\bar{t}\to e/\mu +4$ jets, we show how to reject all but $25\%$ of the background in a data sample while retaining $80\%$ of the signal, without introducing bias into the subsequent mass measurement. The technique used is the Binary Decision Tree. Combining this highly efficient procedure for signal identification with a novel algorithm for top quark reconstruction, we propose a powerful new way to measure the top quark mass.

17 pages, uses revtex macros, postscript figures in .uu format, or available from the Authors.

References in corpus (6)

• Observation of Top Quark Production in Pbar-P Collisions
• Observation of the Top Quark
• CTEQ Parton Distributions and Flavor Dependence of Sea Quarks
• Event shape criteria for single-lepton top signals
• A Comparison of the Use of Binary Decision Trees and Neural Networks in Top Quark Detection
• Further ways to distinguish single-lepton top quark signals from background at the Tevatron

Cited by in corpus (2)

• Jet Algorithms and Top Quark Mass Measurement
• Improving the Measurement of the Top Quark Mass