Bayesian estimation of the specific shear and bulk viscosity of quark–gluon plasma

Bernhard, Jonah E.; Moreland, J. Scott; Bass, Steffen A.

doi:10.1038/s41567-019-0611-8

Cited by 396 publications

(433 citation statements)

References 66 publications

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“…The effects of bulk viscosity should be considered when extracting any transport coefficient from the data [45][46][47].…”

Section: Jhep05(2020)085mentioning

confidence: 99%

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Higher harmonic non-linear flow modes of charged hadrons in Pb-Pb collisions at $$ \sqrt{s_{\mathrm{NN}}} $$ = 5.02 TeV

Acharya¹,

Adamová²,

Adler³

et al. 2020

J. High Energ. Phys.

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Anisotropic flow coefficients, v n , non-linear flow mode coefficients, χ n,mk , and correlations among different symmetry planes, ρ n,mk are measured in Pb-Pb collisions at √ s NN = 5.02 TeV. Results obtained with multi-particle correlations are reported for the transverse momentum interval 0.2 < p T < 5.0 GeV/c within the pseudorapidity interval 0.4 < |η| < 0.8 as a function of collision centrality. The v n coefficients and χ n,mk and ρ n,mk are presented up to the ninth and seventh harmonic order, respectively. Calculations suggest that the correlations measured in different symmetry planes and the non-linear flow mode coefficients are dependent on the shear and bulk viscosity to entropy ratios of the medium created in heavy-ion collisions. The comparison between these measurements and those at lower energies and calculations from hydrodynamic models places strong constraints on the initial conditions and transport properties of the system.

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“…The effects of bulk viscosity should be considered when extracting any transport coefficient from the data [45][46][47].…”

Section: Jhep05(2020)085mentioning

confidence: 99%

“…However, large sets of calculations in many parameter spaces require substantial computing power. In order to constrain the model parameters Bayesian analysis can provide a plausible approach as demonstrated in [45,47]. At present it is limited to low harmonic-order observables, and the extracted parameters have large uncertainties.…”

Section: Jhep05(2020)085mentioning

confidence: 99%

Higher harmonic non-linear flow modes of charged hadrons in Pb-Pb collisions at $$ \sqrt{s_{\mathrm{NN}}} $$ = 5.02 TeV

Acharya¹,

Adamová²,

Adler³

et al. 2020

J. High Energ. Phys.

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show abstract

“…The Bayesian analysis [34][35][36] applies a global fitting to a set of different observables for parameter estimation. In Ref.…”

Section: Introductionmentioning

confidence: 99%

“…In Ref. [36], the crossover type EoS was employed in the hybrid hydrodynamic framework and the event-averaged experimental data (e.g. particle yields, momentum distribution and flow) were used to infer the temperature-dependent shear and bulk viscosity of nuclear matter and other parameters at the same time.…”

Section: Introductionmentioning

confidence: 99%

Identifying the nature of the QCD transition in relativistic collision of heavy nuclei with deep learning

Zhou

Steinheimer

et al. 2020

Eur. Phys. J. C

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Using deep convolutional neural network (CNN), the nature of the QCD transition can be identified from the final-state pion spectra from hybrid model simulations of heavy-ion collisions that combines a viscous hydrodynamic model with a hadronic cascade "after-burner". Two different types of equations of state (EoS) of the medium are used in the hydrodynamic evolution. The resulting spectra in transverse momentum and azimuthal angle are used as the input data to train the neural network to distinguish different EoS. Different scenarios for the input data are studied and compared in a systematic way. A clear hierarchy is observed in the prediction accuracy when using the event-by-event, cascade-coarse-grained and event-fine-averaged spectra as input for the network, which are about 80%, 90% and 99%, respectively. A comparison with the prediction performance by deep neural network (DNN) with only the normalized pion transverse momentum spectra is also made. High-level features of pion spectra captured by a carefully-trained neural network were found to be able to distinguish the nature of the QCD transition even in a simulation scenario which is close to the experiments. trations of the usage of iEBE-VISHNU package and Volodymyr Vovchenko for helpful discussions. This work is supported by the Helmholtz Graduate School HIRe for FAIR (Y. D. and A. M.) , by the F&E Programme of GSI Helmholtz Zentrum für Schwerionenforschung GmbH, Darmstadt (Y. D.), by the Giersch Science Center (Y. D.), by the Walter Greiner Gesellschaft zur Förderung der physikalischen Grundlagenforschung e.V., Frankfurt (Y. D.), by the AI grant of SAMSON AG,

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“…Such a model can then produce predictions for many different observables for each particular set of input parameters. By using such a model in a Bayesian analysis, it is then possible to fit the input parameters to real experimental data, allowing one to learn something about which input parameters fit the data best [196][197][198][199][200][201][202][203][204].…”

Section: Chapter 4 Simulation Of Heavy Ion Collisions With Trajectummentioning

confidence: 99%

Holography in Quark-Gluon Plasma and Neutron Stars

Nijs¹

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In this thesis, QCD is studied from three different directions, with one overarching theme: holography. The holographic duality allows certain strongly coupled QFTs to be described in terms of much simpler classical gravity in one dimension more. The first direction from which QCD is studied in this thesis is by examining the effects of an external magnetic field on a particular holographic model of QCD, yielding interesting qualitative insight. The second approach examines how, in the same model, one can describe dense baryonic configurations, providing a new way to study the matter composing neutron stars. Indeed, the equation of state produced in this way is subsequently used to compute several neutron star properties which are observable, or will be in the near future. The last direction contains no holographic computations per se, but does incorporate several qualitative insights from holography into a new heavy ion code called Trajectum. This will in the near future be used to perform a Bayesian analysis, whereby it is hoped that these qualitative insights from holography can be tested on experimental data, to see how well the ideas coming from holography match up with experiment.

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Bayesian estimation of the specific shear and bulk viscosity of quark–gluon plasma

Cited by 396 publications

References 66 publications

Higher harmonic non-linear flow modes of charged hadrons in Pb-Pb collisions at $$ \sqrt{s_{\mathrm{NN}}} $$ = 5.02 TeV

Higher harmonic non-linear flow modes of charged hadrons in Pb-Pb collisions at $$ \sqrt{s_{\mathrm{NN}}} $$ = 5.02 TeV

Identifying the nature of the QCD transition in relativistic collision of heavy nuclei with deep learning

Holography in Quark-Gluon Plasma and Neutron Stars

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