A new multivariate technique for top quark search

✍ Scribed by Lasse Holmström; Stephan R. Sain; Hannu E. Miettinen

• Publisher: Elsevier Science
• Year: 1995
• Tongue: English
• Weight: 818 KB
• Volume: 88
• Category: Article
• ISSN: 0010-4655
• DOI: 10.1016/0010-4655(95)00040-m

✦ Synopsis

We present a new multivariate event classifier, the PDE classifier, which can be used to identify rare signals in the presence of large backgrounds. The classifier is based on a discriminant function which uses kernel density estimates of the signal and background event densities. The PDE method offers the flexibility of a neural network but is conceptually simpler, theoretically better understood, and easier to optimize in practice. The technique is tested on Monte Carlo data using processes t~ --* e + Et + jets as signal and W + jets --~ e + Et + jets as background. The performance of the PDE classifier is similar to that of a neural network. Both methods outperform conventional analysis.