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.
Effects of Initial Density Fluctuations on Cumulants in Au + Au Collisions at $\sqrt{s_{NN}}$ = 7.7 GeV
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abstract
Within the ultrarelativistic quantum molecular dynamics (UrQMD) model, the effect of initial density fluctuations on cumulants of the net-proton multiplicity distribution in Au + Au Collisions at $\sqrt{s_{NN}}$ = 7.7 GeV was investigated by varying the minimum distance $d_{\rm min}$ between two nucleons in the initialization. It was found that the initial density fluctuations increased with the decrease of $d_{\rm min}$ from 1.6 fm to 1.0 fm, and the influence of $d_{\rm min}$ on the magnitude of the net-proton number fluctuation in a narrow pseudorapidity window ($\Delta \eta \leq$ 4) was negligible even if it indeed affected the density evolution during the collision. At a broad pseudorapidity window ($\Delta \eta \geq$ 4), the cumulant ratios were enlarged when the initial density fluctuations were increased with the smaller value of $d_{\rm min}$, and this enhancement was comparable to that observed in the presence of the nuclear mean-field potential. Moreover, the enhanced cumulants were more evident in collisions with a larger impact parameter. The present work demonstrates that the fingerprint of the initial density fluctuations on the cumulants in a broad pseudorapidity window is clearly visible, while it is not obvious as the pseudorapidity window becomes narrow.
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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.