activity
20182020
most citedDynamical energy loss formalism: from describing suppression patterns to implications for future experiments

3 citations · 3 across the 1 of their papers we have counts for

collaborators

7 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…

q-bio.PE2020

Effects of demographic and weather parameters on COVID-19 basic reproduction number

Igor Salom, Andjela Rodic, Ognjen Milicevic +3

Timely prediction of the COVID-19 progression is not possible without a comprehensive understanding of environmental factors that may affect the infection transmissibility. Studies…

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…

hep-ph2019

Exploring the initial stages in heavy-ion collisions with high-pT RAA and v2 theory and data

Dusan Zigic, Bojana Ilic, Marko Djordjevic +1

Traditionally, low-pT sector is used to infer the features of initial stages before QGP thermalization. On the other hand, recently acquired wealth of high-pT experimental data pav…

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…