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

Preprint

11 March 1996

preprint
Published by arXiv in arXiv

https://doi.org/10.48550/arXiv.hep-ph/9603269

Abstract

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 analyses, from variable selection to systematic errors, are presented. The top--quark search is used as an example to illustrate the problems and proposed solutions.

Keywords

DISCRIMINATING SIGNAL
VARIABLE SELECTION
SYSTEMATIC ERRORS
EVENTS IS STUDIED
BACKGROUND USING
NEURAL NETWORKS
QUARK SEARCH
SIGNAL

All Related Versions

Version 1, 1996-03-11, ArXiv
Published version: Physical Review D, 54 (1), 1233.

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