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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.
The in-medium properties of the vector mesons are known to be modified significantly in hot and dense hadronic matter due to vacuum polarisation e ects from the baryon sector in the Walecka model. The vector meson mass drops significantly in the medium due to the e ects of the Dirac sea. In the variational approach adopted in the present paper, these e ects are taken into account through a realignment of the ground state with baryon condensates. Such a realignment of the ground state becomes equivalent to summing of the baryonic tadpole diagrams in the relativistic Hartree approximation (RHA). The approximation scheme adopted here goes beyond RHA to include quantum e ects from the scalar meson and is nonperturbative and self consistent. It includes multiloop e ects, thus corresponding to a di erent approximation as compared to the one loop approximation of including scalar field quantum corrections. In the present work, we study the properties of the vector mesons in the hot and dense matter as modified due to such quantum correction e ects from the baryon as well as scalar meson sectors. These medium modifications of the properties of the vector mesons are reflected, through the shifting and broadening of the respective peaks, in the low mass dilepton spectra. There is broadening of the peaks due to corrections from scalar meson quantum e ects as compared to the relativistic Hartree approximation. It is seen to be rather prominent for the ! meson in the invariant mass plot. PACS number: 21.65.+f,12.40.Yx