A LightGBM model trained on pion observables from one transport model predicts impact parameters in Au+Au collisions at 4 and 11 GeV with 0.2-0.4 fm error, generalizing to data from other models where polynomial fits fail.
Heavy ion collisions from $\sqrt{s_{NN}}$ of 62.4 GeV down to 4 GeV in the EPOS4 framework
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abstract
The EPOS4 project is an attempt to construct a realistic model for describing relativistic collisions of different systems, from proton-proton ($pp$) to nucleus-nucleus ($AA$), at energies from several TeV per nucleon down to several GeV. We argue that a parallel scattering formalism (as in EPOS4) is relevant for primary scatterings in AA collisions above 4 GeV, whereas sequential scattering (cascade) is appropriate below. We present briefly the basic elements of EPOS4, and then investigate heavy ion collisions from 62.4 GeV down to 4 GeV, to understand how physics changes with energy, studying in particular the disappearance of the fluid component at low energies.
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Machine learning the impact parameter in heavy-ion collisions at $\sqrt{s_{\rm NN}}$ = 4 and 11 GeV: a cross-check study with UrQMD, AMPT, and JAM
A LightGBM model trained on pion observables from one transport model predicts impact parameters in Au+Au collisions at 4 and 11 GeV with 0.2-0.4 fm error, generalizing to data from other models where polynomial fits fail.