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• W2951716910 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 in that respect. A novel input generation for the network is proposed, namely, the transverse and longitudinal momentum distributions of all outgoing (or actually detectable) particles. The neural network approach yields an improvement in performance of a factor of 2 as compared to classical techniques. To achieve this improvement simple network architectures and a 5ifmmodetimeselsetexttimesfi{}5 input grid in (${mathit{p}}_{mathit{t}}$,${mathit{p}}_{mathit{z}}$) space are sufficient. textcopyright{} 1996 The American Physical Society." @default.
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• W2951716910 date "1996-05-01" @default.
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• W2951716910 title "Neural networks for impact parameter determination" @default.
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• W2951716910 doi "https://doi.org/10.1103/physrevc.53.2358" @default.
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