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.
Bass, SA; Bischoff, A; Hartnack, C; Maruhn, JA; Reinhardt, J; Stocker, H; Greiner, W
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