Sprecher
Beschreibung
Jets are excellent probes for studying the deconfined matter formed in heavy ion collisions. Measurements of jet yield and substructure as a function of jet resolution parameter $R$ over a wide range in jet $p_{\mathrm{T}}$ probe the mechanisms underlying the interaction between jets and the QGP, notably the role of opening angle of the hardest jet shower components, and of the angular distribution of medium-induced radiation. In this talk, we will present two measurements of the nuclear modification factor $R_{AA}$ in central Pb-Pb collisions at $\sqrt{s}= 5.02$ TeV with ALICE, addressing the influence of the large uncorrelated background with novel techniques in machine learning and mixed event subtraction. The mixed-event technique, newly introduced in ALICE, enables inclusive jet measurements at low $p_{\mathrm{T}}$ with minimal bias, in a previously unexplored energy regime at the LHC. In addition, the machine learning method enables the measurement of the $R$-dependence of jet suppression for $R=0.6$ down to 40 GeV/c. Finally, we introduce a new infrared and collinear safe measurement of the jet energy flow within jets reconstructed with different resolution parameters $R$. Investigating how the energy is distributed for the same jet with different $R$ allows energy loss to be explored on a jet-by-jet basis instead of between different populations of jets as in inclusive measurements. These results are compared to jet quenching models.
Affiliation
CERN
| Experiment/Theory | ALICE |
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