# Quark Matter 2018

May 13 – 19, 2018
Venice, Italy
Europe/Zurich timezone
The organisers warmly thank all participants for such a lively QM2018! See you in China in 2019!

## Measuring the rate of isotropization of quark-gluon plasma using rapidity correlations

May 14, 2018, 5:50 PM
20m
Sala Perla, 1st Floor (Palazzo del Casinò)

### Sala Perla, 1st Floor

#### Palazzo del Casinò

Parallel Talk Correlations and fluctuations

### Speaker

Prof. George Moschelli (Lawrence Technological University)

### Description

We propose that rapidity dependent momentum correlations can be used to extract the shear relaxation time $\tau_\pi$ of the medium formed in high energy nuclear collisions. The stress-energy tensor in an equilibrium quark-gluon plasma is isotropic, but in nuclear collisions it is likely very far from this state. The relaxation time $\tau_\pi$ characterizes the rate of isotropization and is a transport coefficient as fundamental as the shear viscosity. We show that fluctuations emerging from the initial anisotropy survive to freeze-out, in excess of thermal fluctuations, influencing rapidity correlation patterns. We show that these correlations can be used to extract $\tau_\pi$. In [1] we describe a method for calculating the rapidity dependence of two-particle momentum correlations with a second order, causal, diffusion equation that includes Langevin noise as a source of thermal fluctuations. The causality requirement introduces the relaxation time and we link the shape of the rapidity correlation pattern to its presence. Here we examine how different equations of state and temperature dependent transport coefficients in the presence of realistic hydrodynamic flow influence the estimate of $\tau_\pi$. In comparison to RHIC data, we find that the ratio $\tau_\pi/\nu \approx 5-6$ where $\nu=\eta/sT$ is the kinematic viscosity. We further make predictions for Pb-Pb collisions at the LHC.
[1] S. Gavin, G. Moschelli, C. Zin, Phys. Rev. C 94, 024921 (2016).

Content type Theory Presenter name already specified

### Primary author

Prof. George Moschelli (Lawrence Technological University)

### Co-authors

Sean Gavin (Wayne State University) Christopher Zin (Wayne State University)

### Presentation materials

 Moschelli_QM2018.pdf Moschelli_QM2018.pptx