Neural networks for impact parameter determination

Accurate impact parameter determination in a heavy-ion collision is crucial for almost all further analysis. We investigate the capabilities of an artificial neural network in that respect. First results show that the ne
Accurate impact parameter determination in a heavy-ion collision is crucial for almost all further analysis. We investigate the capabilities of an artificial neural network in that respect. First results show that the neural network is capable of improving the accuracy of the impact parameter determination based on observables such as the flow angle, the average directed inplane transverse momentum and the difference between transverse and longitudinal momenta. However, further investigations are necessary to discover the full potential of the neural network approach.
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Metadaten
Author:Steffen A. Bass, Arnd Bischoff, Christoph Hartnack, Joachim Maruhn, Joachim Reinhardt, Horst Stöcker, Walter Greiner
URN:urn:nbn:de:hebis:30-27026
Parent Title (German):Journal of Physics G: Nuclear and particle physics
Publisher:IOP Publishing
Document Type:Article
Language:English
Date of Publication (online):2006/05/24
Year of first Publication:1994
Publishing Institution:Universitätsbibliothek Johann Christian Senckenberg
Release Date:2006/05/24
Volume:20
Pagenumber:6
First Page:L21
Last Page:L26
HeBIS PPN:192331256
Institutes:Physik
Dewey Decimal Classification:530 Physik
Sammlungen:Universitätspublikationen
Licence (German):License Logo Veröffentlichungsvertrag für Publikationen

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