Neural Networks for Analysis of Top Quark Production

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dc.creatorD0 Collaboration
dc.creatorAbbott, B
dc.date1999-07-21
dc.date.accessioned2026-07-07T03:37:59Z
dc.date.available2026-07-07T03:37:59Z
dc.descriptionNeural networks (NNs) provide a powerful and flexible tool for selecting a signal from a larger background. The D0 collaboration has used them extensively in studying t-tbar decays. NNs were essential to the measurement of the t-tbar production cross section in the all-jets channel (t tbar -> b bbar qqqq, and were also used in the measurement of the mass of the top quark in the lepton+jets channel (t tbar -> b bbar l nu q qbar). This paper will describe two new applications of neural networks to top~quark analysis: the search for single top~quark production, and an effort to increase the sensitivity in the dilepton channel t tbar -> b bbar e mu nu nu beyond that achieved in the published analysis.
dc.description9 pages, 13 figures, submitted to EPS99 and Lepton-Photon99
dc.identifierhttps://arxiv.org/abs/hep-ex/9907041
dc.identifierhttp://arxiv.org/abs/hep-ex/9907041
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/38342
dc.subjectHigh Energy Physics - Experiment
dc.titleNeural Networks for Analysis of Top Quark Production
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