The ALICE Collaboration reports a new differential measurement of inclusive jet suppression using pp and Pb$-$Pb collision data at center-of-mass energy per nucleon-nucleon collision $\sqrt{s_{\rm NN}} = 5.02$ TeV. Charged-particle jets are reconstructed using the anti-$k_{\rm T}$ algorithm with resolution parameters $R =$ 0.2, 0.3, 0.4, 0.5, and 0.6 in pp collisions and $R =$ 0.2, 0.4, 0.6 in central (0$-$10%), semi-central (30$-$50%), and peripheral (60$-$80%) Pb$-$Pb collisions. The analysis uses a novel approach based on machine learning to mitigate the influence of jet background in central heavy-ion collisions, which enables measurements of inclusive jet suppression for jet $p_{\rm T} \geq 40$ GeV/$c$ in central collisions at a resolution parameter of $R = 0.6$. This is the lowest value of jet $p_{\rm T}$ achieved for inclusive jet measurements at $R=0.6$ at the LHC, and is an important step for discriminating different models of jet quenching in the quark-gluon plasma. The transverse momentum spectra, nuclear modification factors, and derived cross section and nuclear modification factor ratios for different jet resolution parameters of charged-particle jets are presented and compared to model predictions. A mild dependence of the nuclear modification factor ratios on collision centrality and resolution parameter is observed. The results are compared to a variety of jet quenching models with varying levels of agreement, demonstrating the effectiveness of this observable to discriminate between models.
Submitted to: PLB
e-Print: arXiv:2303.00592 | PDF | inSPIRE
CERN-EP-2023-027
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