DREENA-C framework: Joint R <inf>AA</inf> and v <inf>2</inf> predictions and implications to QGP tomography

Abstract

© 2019 IOP Publishing Ltd. In this paper, we presented our recently developed Dynamical Radiative and Elastic ENergy loss Approach (DREENA-C) framework, which is a fully optimized computational suppression procedure based on our state-of-the-art dynamical energy loss formalism in constant temperature finite size QCD medium. With this framework, we have generated, for the first time, joint R AA and v 2 predictions within our dynamical energy loss formalism. The predictions are generated for both light and heavy flavor probes, and different centrality regions in Pb + Pb collisions at the LHC, and compared with the available experimental data. While R AA predictions agree with experimental data, v 2 predictions qualitatively agree with, but are quantitatively visibly above, the experimental data (in disagreement with other models, which underestimate v 2). Consistently with numerical predictions, through simple analytic analysis, we show that R AA is insensitive to medium evolution (though highly sensitive to energy loss mechanisms), while v 2 is highly sensitive to the evolution. As a major consequence for precision quark-gluon plasma (QGP) tomography, this then leaves a possibility to calibrate energy loss models on R AA data, while using v 2 to constrain QGP parameters that are in agreement with both high and low p ⊥ data.