STAR reports energy-dependent variances and covariances of [p_T] and v_n^2 in Au+Au collisions from 14.6 to 200 GeV, with the dimensionless ratio remaining similar across energies.
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A PINN constrained by the two-component multiplicity model learns the hard-scattering fraction from Zr+Zr events and predicts N_ch more accurately than a data-driven NN on unseen Ru+Ru and Au+Au collisions.
A review of thermal modifications to light and heavy hadron properties via imaginary-time formalism, effective field theories, unitarized approaches, and lattice QCD, with links to heavy-ion phenomenology.
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Beam-energy dependence of correlations between mean transverse momentum and anisotropic flow of charged particles in Au+Au collisions at RHIC
STAR reports energy-dependent variances and covariances of [p_T] and v_n^2 in Au+Au collisions from 14.6 to 200 GeV, with the dimensionless ratio remaining similar across energies.
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Physics-informed neural network (PINN) modeling of charged particle multiplicity using the two-component framework in heavy-ion collisions: A comparison with data-driven neural networks
A PINN constrained by the two-component multiplicity model learns the hard-scattering fraction from Zr+Zr events and predicts N_ch more accurately than a data-driven NN on unseen Ru+Ru and Au+Au collisions.
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Hadron properties at finite temperature
A review of thermal modifications to light and heavy hadron properties via imaginary-time formalism, effective field theories, unitarized approaches, and lattice QCD, with links to heavy-ion phenomenology.