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Register a new userThe importance of the bulk viscosity of QCD in ultrarelativistic heavy-ion collisions
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We investigate the consequences of a nonzero bulk viscosity coefficient on the transverse momentum spectra, azimuthal momentum anisotropy, and multiplicity of charged hadrons produced in heavy ion collisions at LHC energies. The agreement between a realistic 3D hybrid simulation and the experimentally measured data considerably improves with the addition of a bulk viscosity coefficient for strongly interacting matter. This paves the way for an eventual quantitative determination of several QCD transport coefficients from the experimental heavy ion and hadron-nucleus collision programs.
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We investigate the influence of a temperature-dependent shear viscosity over entropy density ratio eta/s on the transverse momentum spectra and elliptic flow of hadrons in ultrarelativistic heavy-ion collisions. We find that the elliptic flow in sqrt(s_NN) = 200 GeV Au+Au collisions at RHIC is dominated by the viscosity in the hadronic phase and in the phase transition region, but largely insensitive to the viscosity of the quark-gluon plasma (QGP). At the highest LHC energy, the elliptic flow becomes sensitive to the QGP viscosity and insensitive to the hadronic viscosity.
We explore the influence of a temperature-dependent shear viscosity over entropy density ratio $eta/s$ on the azimuthal anisotropies v_2 and v_4 of hadrons at various rapidities. We find that in Au+Au collisions at full RHIC energy, $sqrt{s_{NN}}=200$ GeV, the flow anisotropies are dominated by hadronic viscosity at all rapidities, whereas in Pb+Pb collisions at the LHC energy, $sqrt{s_{NN}}=2760$ GeV, the flow coefficients are affected by the viscosity both in the plasma and hadronic phases at midrapidity, but the further away from midrapidity, the more dominant the hadronic viscosity is. We find that the centrality and rapidity dependence of the elliptic and quadrangular flows can help to distinguish different parametrizations of $(eta/s)(T)$. We also find that at midrapidity the flow harmonics are almost independent of the decoupling criterion, but show some sensitivity to the criterion at back- and forward rapidities.
A simple approach is proposed allowing actual calculations of the preequilibrium dynamics in ultrarelativistic heavy-ion collisions to be performed for a far-from-equilibrium initial state. The method is based on the phenomenological macroscopic equations that describe the relaxation dynamics of the energy-momentum tensor and are motivated by Boltzmann kinetics in the relaxation-time approximation. It gives the possibility to match smoothly a nonthermal initial state to the hydrodynamics of the quark gluon plasma. The model contains two parameters, the duration of the prehydrodynamic stage and the initial value of the relaxation-time parameter, and allows one to assess the energy-momentum tensor at a supposed time of initialization of the hydrodynamics.
We present measurements of the pseudorapidity distribution of primary charged particles produced in Au+Au collisions at three energies, sqrt(s_{NN}) = 19.6, 130, and 200 GeV, for a range of collision centralities. The centrality dependence is shown to be non-trivial: the distribution narrows for more central collisions and excess particles are produced at high pseudorapidity in peripheral collisions. For a given centrality, however, the distributions are found to scale with energy according to the limiting fragmentation hypothesis. The universal fragmentation region described by this scaling grows in pseudorapidity with increasing collision energy, extending well away from the beam rapidity and covering more than half of the pseudorapidity range over which particles are produced. This approach to a universal limiting curve appears to be a dominant feature of the pseudorapidity distribution and therefore of the total particle production in these collisions.
In this proceeding, we review our recent work using deep convolutional neural network (CNN) to identify the nature of the QCD transition in a hybrid modeling of heavy-ion collisions. Within this hybrid model, a viscous hydrodynamic model is coupled with a hadronic cascade after-burner. As a binary classification setup, we employ two different types of equations of state (EoS) of the hot medium in the hydrodynamic evolution. The resulting final-state pion spectra in the transverse momentum and azimuthal angle plane are fed to the neural network as the input data in order to distinguish different EoS. To probe the effects of the fluctuations in the event-by-event spectra, we explore different scenarios for the input data and make a comparison in a systematic way. We observe a clear hierarchy in the predictive power when the network is fed with the event-by-event, cascade-coarse-grained and event-fine-averaged spectra. The carefully-trained neural network can extract high-level features from pion spectra to identify the nature of the QCD transition in a realistic simulation scenario.
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