Measurement of jet pT correlations in Pb + Pb and pp collisions at sNN=2.76 TeVwith the ATLAS detector

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Bibtex

@article{7d842ab0bcde4a9c963703858d73722d,
title = "Measurement of jet pT correlations in Pb + Pb and pp collisions at sNN=2.76 TeVwith the ATLAS detector",
abstract = "Measurements of dijet pT correlations in Pb+Pb and pp collisions at a nucleon–nucleon centre-of-mass energy of sNN=2.76 TeV are presented. The measurements are performed with the ATLAS detector at the Large Hadron Collider using Pb+Pb and pp data samples corresponding to integrated luminosities of 0.14 nb−1 and 4.0 pb−1, respectively. Jets are reconstructed using the anti-kt algorithm with radius parameter values R=0.3 and R=0.4. A background subtraction procedure is applied to correct the jets for the large underlying event present in Pb+Pb collisions. The leading and sub-leading jet transverse momenta are denoted pT1 and pT2. An unfolding procedure is applied to the two-dimensional (pT1,pT2) distributions to account for experimental effects in the measurement of both jets. Distributions of (1/N)dN/dxJ, where xJ=pT2/pT1, are presented as a function of pT1 and collision centrality. The distributions are found to be similar in peripheral Pb+Pb collisions and pp collisions, but highly modified in central Pb+Pb collisions. Similar features are present in both the R=0.3 and R=0.4 results, indicating that the effects of the underlying event are properly accounted for in the measurement. The results are qualitatively consistent with expectations from partonic energy loss models. {\circledC} 2017 The Author",
author = "{ATLAS Collaboration} and M Aaboud and Torsten {\AA}kesson and Simona Bocchetta and Lene Bryngemark and Caterina Doglioni and Vincent Hedberg and G{\"o}ran Jarlskog and Charles Kalderon and Else Lytken and Ulf Mj{\"o}rnmark and Oxana Smirnova and Oleksandr Viazlo",
year = "2017",
doi = "10.1016/j.physletb.2017.09.078",
language = "English",
volume = "774",
pages = "379--402",
journal = "Physics Letters B",
issn = "0370-2693",
publisher = "Elsevier",

}