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 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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Author:Steffen A. BassORCiDGND, Arnd Bischoff, Christoph HartnackORCiD, Joachim MaruhnORCiDGND, Joachim ReinhardtGND, Horst StöckerORCiDGND, Walter GreinerGND
Parent Title (German):Journal of Physics G: Nuclear and particle physics
Publisher:IOP Publishing
Document Type:Article
Date of Publication (online):2006/05/24
Year of first Publication:1994
Publishing Institution:Universitätsbibliothek Johann Christian Senckenberg
Release Date:2006/05/24
Page Number:6
First Page:L21
Last Page:L26
Institutes:Physik / Physik
Dewey Decimal Classification:5 Naturwissenschaften und Mathematik / 53 Physik / 530 Physik
Licence (German):License LogoDeutsches Urheberrecht