# Quantifying properties of hot and dense QCD matter through systematic model-to-data comparison

@article{Bernhard2015QuantifyingPO, title={Quantifying properties of hot and dense QCD matter through systematic model-to-data comparison}, author={Jonah Bernhard and Peter William Marcy and Christopher E. Coleman-Smith and Snehalata V. Huzurbazar and Robert L. Wolpert and Steffen A. Bass}, journal={Physical Review C}, year={2015}, volume={91}, pages={054910} }

We systematically compare an event-by-event heavy-ion collision model to data from the CERN Large Hadron Collider. Using a general Bayesian method, we probe multiple model parameters including fundamental quark-gluon plasma properties such as the specific shear viscosity η/s, calibrate the model to optimally reproduce experimental data, and extract quantitative constraints for all parameters simultaneously. Furthermore, the method is universal and easily extensible to other data and collision…

## Figures and Tables from this paper

## 39 Citations

Probing Quark-Gluon-Plasma properties with a Bayesian model-to-data comparison

- Physics
- 2016

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…

Investigating the collision energy dependence of η/s in the beam energy scan at the BNL Relativistic Heavy Ion Collider using Bayesian statistics

- Physics
- 2018

We determine the probability distributions of the shear viscosity over the entropy density ratio η/s in the quark-gluon plasma formed in Au + Au collisions at sNN=19.6,39, and 62.4GeV, using Bayesian…

Determining the diffusivity for light quarks from experiment

- Physics
- 2019

Charge balance functions reflect the evolution of charged pair correlations throughout the stages of pair production, dynamical diffusion, and hadronization in heavy-ion collisions. Microscopic…

Determining the jet transport coefficient $\hat{q}$ of the quark-gluon plasma using Bayesian parameter estimation

- Physics
- 2021

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…

Data-driven analysis for the temperature and momentum dependence of the heavy-quark diffusion coefficient in relativistic heavy-ion collisions

- Physics
- 2017

By applying a Bayesian model-to-data analysis, we estimate the temperature and momentum dependence of the heavy quark diffusion coefficient in an improved Langevin framework. The posterior range of…

## References

SHOWING 1-10 OF 36 REFERENCES

Gaussian Processes for Machine Learning

- Computer ScienceAdaptive computation and machine learning
- 2009

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.

“A and B”:

- PhysicsSophonisba Breckinridge
- 2019

Direct fabrication of large micropatterned single crystals. p1205 21 Feb 2003. (news): Academy plucks best biophysicists from a sea of mediocrity. p994 14 Feb 2003.

and Y

- Nara, Phys.Rev. C74, 044905
- 2006

PASP 125

- 306
- 2013

and H

- Wang,
- 2015

C

- Coleman-Smith, et al., Phys.Rev. C89, 034917
- 2014

S

- Bass, et al.,
- 2014

and M

- O’Neil,
- 2014

and S

- M. Wild,
- 2014