Neural Networks for Impact Parameter Determination

Details Neural Networks for Impact Parameter Determination Neural Networks for Impact Parameter Determination

1996-01-17

arxiv.org/abs/nucl-th/9601024v1

Phys.Rev.C53:2358-2363,1996

Physics

Nuclear Physics

Nuclear Theory

Phys. Rev. C in print. Postscript-file also available at http://www.th.physik.uni-frankfurt.de/~bass/pub.html

Scientific paper

10.1103/PhysRevC.53.2358

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 by 5 input grid in (p_t,p_z) space are sufficient.

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