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

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 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.