Please use this identifier to cite or link to this item:
Title: Enhancing the top-quark signal at Fermilab Tevatron using neural nets
Author: Ametller, Ll.
Garrido Beltrán, Lluís
Talavera Sánchez, Pedro
Keywords: Partícules (Física nuclear)
Física matemàtica
Particles (Nuclear physics)
Mathematical physics
Issue Date: 1994
Publisher: The American Physical Society
Abstract: We show, in agreement with previous studies, that neural nets can be useful for top-quark analysis at the Fermilab Tevatron. The main features of tt¯ and background events in a mixed sample are projected on a single output, which controls the efficiency, purity, and statistical significance of the tt¯ signal. We consider a feed-forward multilayer neural net for the CDF reported top-quark mass, using six kinematical variables as inputs. Our main results are based on the exhaustive comparison of the neural net performances with those obtainable from the standard experimental analysis, by imposing different sets of linear cuts over the same variables, showing how the neural net approach improves the standard analysis results.
Note: Reproducció digital del document publicat en format paper, proporcionada per PROLA i
It is part of: Physical Review D, 1994, vol. 50, núm. 9, p. R5473-R5477
Related resource:
ISSN: 0556-2821
Appears in Collections:Articles publicats en revistes (Física Quàntica i Astrofísica)

Files in This Item:
File Description SizeFormat 
137386.pdf980.99 kBAdobe PDFView/Open

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.