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In this talk we presented a novel technique, based on Deep Learning, to determine the impact parameter of nuclear collisions at the CBM experiment. PointNet based Deep Learning models are trained on UrQMD followed by CBMRoot simulations of Au+Au collisions at 10 AGeV to reconstruct the impact parameter of collisions from raw experimental data such as hits of the particles in the detector planes, tracks reconstructed from the hits or their combinations. The PointNet models can perform fast, accurate, event-by-event impact parameter determination in heavy ion collision experiments. They are shown to outperform a simple model which maps the track multiplicity to the impact parameter. While conventional methods for centrality classification merely provide an expected impact parameter distribution for a given centrality class, the PointNet models predict the impact parameter from 2–14 fm on an event-by-event basis with a mean error of −0.33 to 0.22 fm.
The HADES experiment provides a large acceptance combined with a high mass resolution and therefore makes it possible to study dielectron and hadron production in heavy-ion collisions with unprecedented precision. With the high statistics of seven billion Au+Au collisions at 1.23 AGeV recorded in 2012 the investigation of collective effects and particle correlations is possible with unprecedented accuracy. We present multi-differential data on directed (v1) and elliptic (v2) flow, and the first measurement of triangular flow (v3), of protons and deuterons.
HADES has a large acceptance combined with a good mass-resolution and therefore allows the study of dielectron and hadron production in heavy-ion collisions with unprecedented precision. With the statistics of seven billion Au-Au collisions at 1.23A GeV recorded in 2012, the investigation of higher-order flow harmonics is possible. At the BEVALAC and SIS18 directed and elliptic flow has been measured for pions, charged kaons, protons, neutrons and fragments, but higher-order harmonics have not yet been studied. They provide additional important information on the properties of the dense hadronic medium produced in heavy-ion collisions. We present here a high-statistics, multidifferential measurement of v1 and v2 for protons in Au+Au collisions at 1.23A GeV.