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Discriminating signal from background using neural networks: Application to top-quark search at the Fermilab Tevatron

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The application of neural networks in high energy physics to the separation of signal from background events is studied. A variety of problems usually encountered in this sort of analysis, from variable selection to systematic errors, are presented. The top-quark search is used as an example to illustrate the problems and proposed solutions.

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Reproducció digital del document publicat en format paper, proporcionada per PROLA i http://dx.doi.org/10.1103/PhysRevD.54.1233

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Articles publicats en revistes (Física Quàntica i Astrofísica)

# metadata.dc.title[].value
Discriminating signal from background using neural networks: Application to top-quark search at the Fermilab Tevatron