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Title: Neural Networks for Analysis of Top Quark Production

Abstract

Neural 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{anti t} decays. NNs were essential to the measurement of the t{anti t} production cross section in the all-jets channel (t{anti t} {yields} b {anti b}qqqq), and were also used in the measurement of the mass of the top quark in the lepton+jets channel (t{anti t} {yields} b{anti b}l{nu}q{anti q}). 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{anti t} {yields} b{anti b}e{anti {mu}}{nu}{anti {nu}} beyond that achieved in the published analysis.

Authors:
Publication Date:
Research Org.:
Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
9370
Report Number(s):
FERMILAB-Conf-99/206-E
ON: DE00009370
DOE Contract Number:  
AC02-76CH03000
Resource Type:
Conference
Resource Relation:
Conference: EPS-HEP99, Tampere, Finland, July 15-21, 1999
Country of Publication:
United States
Language:
English
Subject:
66 PHYSICS; Neural Networks; T Quarks; Particle Production

Citation Formats

B. Abbott et al. Neural Networks for Analysis of Top Quark Production. United States: N. p., 1999. Web.
B. Abbott et al. Neural Networks for Analysis of Top Quark Production. United States.
B. Abbott et al. Wed . "Neural Networks for Analysis of Top Quark Production". United States. https://www.osti.gov/servlets/purl/9370.
@article{osti_9370,
title = {Neural Networks for Analysis of Top Quark Production},
author = {B. Abbott et al.},
abstractNote = {Neural 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{anti t} decays. NNs were essential to the measurement of the t{anti t} production cross section in the all-jets channel (t{anti t} {yields} b {anti b}qqqq), and were also used in the measurement of the mass of the top quark in the lepton+jets channel (t{anti t} {yields} b{anti b}l{nu}q{anti q}). 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{anti t} {yields} b{anti b}e{anti {mu}}{nu}{anti {nu}} beyond that achieved in the published analysis.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {1999},
month = {8}
}

Conference:
Other availability
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