An effective model for entropy deposition in high-energy pp, pA, and AA collisions

By J. Moreland, Jonah E. Bernhard, Steffen A. Bass. 2014

204 citations recorded by the source corpus.

We introduce a new parametric initial-condition model for high-energy nuclear collisions based on eikonal entropy deposition via a ``reduced-thickness'' function. The model simultaneously describes experimental proton-proton, proton-nucleus, and nucleus-nucleus multiplicity distributions and generates nucleus-nucleus eccentricity harmonics consistent with experimental flow constraints. In addition, the model is compatible with ultracentral uranium-uranium data unlike existing models that include binary collision terms.

Subfields: Aerospace Engineering, Nuclear and High Energy Physics

View Paper: https://www.semanticscholar.org/paper/8a314dc4bb142f99f2cecb349eae56ad6eaa98b3

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Aerospace Engineering

1. K. Gajdošová
2. Huichao Song
3. You Zhou

In Nuclear and High Energy Physics

1. K. Gajdošová
2. You Zhou
3. Huichao Song
4. Paul Romatschke
5. Harvey B. Meyer

Citations in the corpus

• Collective flow and hydrodynamics in large and small systems at the LHC (2017, methodology): “The recently developed TRENTo model [113] is a parametric initial condition model based on the eikonal entropy deposition via a reduced thickness function.”