Deep learning extracts a unified in-medium heavy quark potential from multi-energy bottomonium data, finding the real part close to vacuum Cornell form with weak screening while the imaginary part dominates suppression.
In-Medium Effects on Charmonium Production in Heavy-Ion Collisions
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abstract
Charmonium production in heavy-ion collisions is investigated within a kinetic theory framework incorporating in-medium properties of open- and hidden-charm states in line with recent QCD lattice calculations. A continuously decreasing open-charm threshold across the phase boundary of hadronic and quark-gluon matter is found to have important implications for the equilibrium abundance of charmonium states. The survival of $J/\psi$ resonance states above the transition temperature enables their recreation also in the Quark-Gluon Plasma. Including effects of chemical and thermal off-equilibrium, we compare our model results to available experimental data at CERN-SPS and BNL-RHIC energies. In particular, earlier found discrepancies in the $\psi'/\psi$ ratio can be resolved.
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A semiclassical transport model using lattice-constrained T-matrix rates and viscous hydrodynamics reproduces the centrality dependence of bottomonium yields in 5.02 TeV Pb-Pb collisions within uncertainties.
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Unified Extraction of In-Medium Heavy Quark Potentials from RHIC to LHC Energies via Deep Learning
Deep learning extracts a unified in-medium heavy quark potential from multi-energy bottomonium data, finding the real part close to vacuum Cornell form with weak screening while the imaginary part dominates suppression.
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Bottomonium transport in a strongly coupled quark-gluon plasma
A semiclassical transport model using lattice-constrained T-matrix rates and viscous hydrodynamics reproduces the centrality dependence of bottomonium yields in 5.02 TeV Pb-Pb collisions within uncertainties.