Neural networks for impact parameter determination

Abstract: An accurate impact parameter determination in a heavy ion collision is crucial for almost all further analysis. The capabilities of an artificial neural network are investigated to that respect. A novel input g
Abstract: An accurate impact parameter determination in a heavy ion collision is crucial for almost all further analysis. The capabilities of an artificial neural network are investigated to that respect. A novel input generation for the network is proposed, namely the transverse and longitudinal momentum distribution of all outgoing (or actually detectable) particles. The neural network approach yields an improvement in performance of a factor of two as compared to classical techniques. To achieve this improvement simple network architectures and a 5 × 5 input grid in (pt, pz) space are suffcient.
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Metadaten
Author:Steffen A. Bass, A. Bischoff, Joachim A. Maruhn, Horst Stöcker, Walter Greiner
URN:urn:nbn:de:hebis:30-24030
ArXiv Id:http://arxiv.org/abs/9601024v1
Document Type:Preprint
Language:English
Date of Publication (online):2006/01/23
Year of first Publication:1996
Publishing Institution:Univ.-Bibliothek Frankfurt am Main
Release Date:2006/01/23
Tag:Kollisionen schwerer Ionen ; heiße und dichte Kernmaterie
heavy ion collisions ; hot and dense nuclear matter
Pagenumber:18
First Page:1
Last Page:18
Source:Phys.Rev.C53:2358-2363,1996 ; http://arxiv.org/abs/nucl-th/9601024
HeBIS PPN:185203264
Institutes:Physik
Dewey Decimal Classification:530 Physik
Sammlungen:Universitätspublikationen
Licence (German):License Logo Veröffentlichungsvertrag für Publikationen

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