# QM 2022

Apr 4 – 10, 2022
Auditorium Maximum UJ
Europe/Warsaw timezone
Proceedings submission deadline extended to August 15, 2022

## First Results for the New Trento-3D Initial-Conditions Ansatz

Apr 6, 2022, 7:18 PM
4m
Poster Initial state physics and approach to thermal equilibrium

### Speaker

Derek Soeder (Duke University)

### Description

Trento-3D is a parametric initial condition model, specifically designed for rapidly generating 3D energy distributions to initialize fully (3+1)-dimensional, event-by-event hydrodynamic simulations of ultrarelativistic heavy-ion collisions. Trento-3D builds upon the well-established T${}_\mathrm{R}$ENTo model [1], which samples nuclear configuration with subnucleonic structure and determines nucleon participation at the instant of collision. In Trento-3D, the total energy deposition is then divided among a central fireball near midrapidity and two fragmentation regions motivated by the limiting fragmentation hypothesis [2]. This extension, with a moderate number of parameters, allows for the faithful simulation of rapidity-dependent observables for a wide variety of collision systems over the gamut of ultrarelativistic energies.

In this presentation, we briefly describe the Trento-3D model and present first results of an ongoing, extensive calibration, demonstrating the capabilities of the model to describe various observables--such as yields, eccentricities, and derived quantities--as functions of rapidity. We explore the use of a (1+1)D linearized hydrodynamics model and the Cooper-Frye particlization procedure for conversion from 3D initial conditions to final-state, rapidity-dependent observables at significantly reduced computational cost. We validate these results vis-à-vis the MUSIC (3+1)D hydrodynamic code and offer predictions on future results and capabilities.

[1] J. S. Moreland, J. E. Bernhard, and S. A. Bass, Phys. Rev. C 92, 011901 (2015).
[2] J. Benecke et al., Phys. Rev. 188, 2159 (1969).

### Primary author

Derek Soeder (Duke University)

### Co-authors

Weiyao Ke (Los Alamos National Laboratory) Jean-Francois Paquet (Duke University) Steffen A. Bass (Duke University)