Identification of Additional Jets in the ttbar-bbbar Events by Using Deep Neural Network

Abstract

In the top quark pair production in association with the Higgs boson decaying to a b quark pair (tt¯H(bb¯) ), the final state has an irreducible nonresonant background from the production of a top quark pair in association with a b quark pair (tt¯bb¯). Therefore, understanding of the tt¯bb¯ process precisely in particular differential cross-section as functions of the properties of the additional b jets not from the top quark decay is essential for improving the sensitivity of a search for the tt¯H(bb¯) process. The two additional b jets can be identified by using various approaches. In this paper, the performances are compared quantitatively in the lepton+jets decay channel in terms of the matching efficiency of assigning two additional b jets as a figure of merit. We showed that a matching efficiency of around 40% could be achieved using a deep neural network method. In the events with at least 4 b jets, this performance is 8% better than that achieved using minimum △R(b,b¯) method. This is consistent with the boosted decision tree method within its statistical uncertainty.