activity
20112020
most citedDynamical energy loss formalism: from describing suppression patterns to implications for future experiments

3 citations · 3 across the 2 of their papers we have counts for

collaborators

9 papers

nucl-th2020

From high theory and data to inferring anisotropy of Quark-Gluon Plasma

Magdalena Djordjevic, Stefan Stojku, Dusan Zigic +5

High theory and data are commonly used to study high parton interactions with QGP, while low data and corresponding models are employed to infer QGP b…

nucl-th20203 cited

Dynamical energy loss formalism: from describing suppression patterns to implications for future experiments

Magdalena Djordjevic, Dusan Zigic, Bojana Blagojevic +3

Understanding properties of Quark-Gluon Plasma requires an unbiased comparison of experimental data with theoretical predictions. To that end, we developed the dynamical energy los…

nucl-th2020

Temperature dependence of of strongly interacting matter: effects of the equation of state and the parametric form of

Jussi Auvinen, Kari J. Eskola, Pasi Huovinen +3

We investigate the temperature dependence of the shear viscosity to entropy density ratio using a piecewise linear parametrization. To determine the optimal values of the par…

hep-ph2018

Temperature dependence of : uncertainties from the equation of state

Jussi Auvinen, Kari J. Eskola, Pasi Huovinen +3

We perform a global model-to-data comparison on Au+Au collisions at GeV and Pb+Pb collisions at TeV and TeV, using a 2+1D hydrodynamics model with…

nucl-th2018

How to test path-length dependence in energy loss mechanisms: analysis leading to a new observable

Magdalena Djordjevic, Dusan Zigic, Marko Djordjevic +1

When traversing QCD medium, high partons lose energy, which is typically measured by suppression, and also predicted by various energy loss models. A crucial test of diff…

nucl-th2018

Joint and predictions for collisions at the LHC within DREENA-C framework

Dusan Zigic, Igor Salom, Jussi Auvinen +2

In this paper, we presented our recently developed DREENA-C framework, which is a fully optimized computational suppression procedure based on our state-of-the-art dynamical energy…