# Quark Matter 2017

5-11 February 2017
Hyatt Regency Chicago
America/Chicago timezone

## Constraints on 3d-initial condition from experimental data and systematic predictions of longitudinal observables

Not scheduled
2h 30m
Hyatt Regency Chicago

#### Hyatt Regency Chicago

151 East Wacker Drive Chicago, Illinois, USA, 60601
Board: F16
Poster

### Speaker

Weiyao Ke (Duke University)

### Description

The description of asymmetric collision systems and longitudinal fluctuations in AA collisions requires a 3D initial condition model consistent with both large and small systems.
Particularly, longitudinal fluctuations lead to event plane decorrelations that impact both soft observables and hard-soft correlation calculations.

In this work, T\raisebox{-0.5ex}{R}ETNo, a parametric initial condition model formulated at mid-rapidity, is extended to include longitudinal dependence.
The local longitudinal entropy deposition as a function of space-time rapidity is characterized by its first three rapidity-cumulants, namely the mean, width and skewness, whose dependencies on local participant densities are parametrized in two ways.

The model parameters introduced in this procedure are calibrated by a Bayesian model-to-data comparison using the $dN_{\text{ch, PbPb}}/d\eta$ from ALICE and the $dN_{\text{ch, pPb}}/d\eta$ from ATLAS simultaneously.
The two different parametrizations are investigated and by comparing 3d-T\raisebox{-0.5ex}{R}ENTo +hydro+UrQMD calculations of the pseudorapidity correlation observable $\langle a_1^2\rangle$ with ATLAS measurement and it is found that the data clearly favors one parametrization over the other.

After calibrating the initial condition model on selected multiplicity observables ($dN_{\text{ch, PbPb}}/d\eta$ and $\langle a_1^2\rangle$),
we calculate pseudorapidity differential flows, event plane decorrelations and compare with available data from ALICE and CMS as a validation of our parametric model.
Finally, the pseudorapidity dependence of symmetric flow correlation cumulants is predicted, since these observables should be very sensitive to the event-by-event initial state geometry.

Collaboration Not applicable Correlations and Fluctuations

### Primary author

Weiyao Ke (Duke University)

### Co-authors

Scott Moreland (Duke University)