Applying Bayesian parameter estimation to relativistic heavy-ion collisions: simultaneous characterization of the initial state and quark-gluon plasma medium

@article{Bernhard2016ApplyingBP,
  title={Applying Bayesian parameter estimation to relativistic heavy-ion collisions: simultaneous characterization of the initial state and quark-gluon plasma medium},
  author={Jonah Bernhard and J. Scott Moreland and Steffen A. Bass and Jia Liu and Ulrich Heinz},
  journal={Physical Review C},
  year={2016},
  volume={94},
  pages={024907}
}
We quantitatively estimate properties of the quark-gluon plasma created in ultrarelativistic heavy-ion collisions utilizing Bayesian statistics and a multiparameter model-to-data comparison. The study is performed using a recently developed parametric initial condition model, TRENTo, which interpolates among a general class of particle production schemes, and a modern hybrid model which couples viscous hydrodynamics to a hadronic cascade. We calibrate the model to multiplicity, transverse… 
Bayesian estimation of the specific shear and bulk viscosity of the quark-gluon plasma with additional flow harmonic observables
The transport properties of the strongly-coupled quark-gluon plasma created in ultra-relativistic heavy-ion collisions are extracted by Bayesian parameter estimate methods with the latest collision
Probing Quark-Gluon-Plasma properties with a Bayesian model-to-data comparison
Relativistic heavy-ion collisions are believed to be able to create in laboratories QuarkGluon Plasma (QGP), a state of matter which the early universe was once in. Given the theoretical difficulty
Bayesian parameter estimation for relativistic heavy-ion collisions
I develop and apply a Bayesian method for quantitatively estimating properties of the quark-gluon plasma (QGP), an extremely hot and dense state of fluid-like matter created in relativistic heavy-ion
Determining the jet transport coefficient $\hat{q}$ of the quark-gluon plasma using Bayesian parameter estimation
We present a new determination of q̂, the jet transport coefficient of the quark-gluon plasma. Using the JETSCAPE framework, we use Bayesian parameter estimation to constrain the dependence of q̂ on
Bayesian estimation of the specific shear and bulk viscosity of quark–gluon plasma
Ultrarelativistic collisions of heavy atomic nuclei produce an extremely hot and dense phase of matter, known as quark–gluon plasma (QGP), which behaves like a near-perfect fluid with the smallest
...
...

References

SHOWING 1-10 OF 98 REFERENCES
Event-by-event Hydrodynamic Simulations for Relativistic Heavy-ion Collisions
In this thesis, I show my Ph.D. work on event-by-event hydrodynamic simulations for relativistic heavy-ion collision. I show that event-by-event hydrodynamic simulations have become an indispensable
[C]
  • Thomas de Quincey
  • Physics
    The Works of Thomas De Quincey, Vol. 1: Writings, 1799–1820
  • 2000
In supernova (SN) spectroscopy relatively little attention has been given to the properties of optically thick spectral lines in epochs following the photosphere’s recession. Most treatments and
Gaussian Processes for Machine Learning
TLDR
The treatment is comprehensive and self-contained, targeted at researchers and students in machine learning and applied statistics, and deals with the supervised learning problem for both regression and classification.
Ann
Aaron Beck’s cognitive therapy model has been used repeatedly to treat depression and anxiety. The case presented here is a 34-year-old female law student with an adjustment disorder with mixed
arXiv:1407.6387 [hep-lat
  • (HotQCD), Phys. Rev. D90,
  • 2014
arXiv:1012.1657 [nucl-ex
  • (ALICE), Phys. Rev. Lett. 106,
  • 2011
Phys
  • Rev. C92, 011901
  • 2015
arXiv:1512.06104 [nucl-ex
  • (ALICE), Phys. Rev. Lett. 116,
  • 2016
arXiv:1509.06727 [nucl-ex
  • (PHENIX), Phys. Rev. C93,
  • 2016
Phys
  • Rev. Lett. 115, 132301
  • 2015
...
...