TL;DR
This paper reports measurements of top quark pair and single top production cross sections at Fermilab's D0 experiment, utilizing advanced neural network and multivariate techniques to improve signal identification at 1.96 TeV.
Contribution
It introduces novel multivariate analysis methods, including neural networks, for more accurate measurement of top quark production cross sections at the Tevatron.
Findings
Measured ttbar production cross section at 1.96 TeV.
Used neural networks to identify b-quark jets.
Presented new measurements of single top production.
Abstract
We report on measurements of the ttbar production cross section at a center-of-mass energy of 1.96 TeV at the D0 experiment during Run II of the Fermilab Tevatron collider. We use candidate events in lepton+jets and dilepton final states. In the most sensitive channel (lepton+jets channel), a neural network algorithm that uses lifetime information to identify b-quark jets is used to distinguish signal from background processes. We also present measurements of single top quark production at D0 using several multivariate techniques to separate signal from background.
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Taxonomy
TopicsParticle physics theoretical and experimental studies · Particle Detector Development and Performance · Superconducting Materials and Applications