Production of leading charged particles and leading charged-particle jets at small transverse momenta in pp collisions at sqrt(s) = 8 TeV

The CMS collaboration Khachatryan, Vardan ; Sirunyan, Albert M ; Tumasyan, Armen ; et al.
Phys.Rev.D 92 (2015) 112001, 2015.
Inspire Record 1380605 DOI 10.17182/hepdata.70721

The per-event yield of the highest transverse momentum charged particle and charged-particle jet, integrated above a given pt(min) threshold starting at pt(min) = 0.8 and 1 GeV, respectively, is studied in pp collisions at sqrt(s) = 8 TeV. The particles and the jets are measured in the pseudorapidity ranges abs(eta) < 2.4 and 1.9, respectively. The data are sensitive to the momentum scale at which parton densities saturate in the proton, to multiple partonic interactions, and to other key aspects of the transition between the soft and hard QCD regimes in hadronic collisions.

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Jet and underlying event properties as a function of particle multiplicity in proton-proton collisions at sqrt(s) = 7 TeV

The CMS collaboration Chatrchyan, Serguei ; Khachatryan, Vardan ; Sirunyan, Albert M ; et al.
Eur.Phys.J.C 73 (2013) 2674, 2013.
Inspire Record 1261026 DOI 10.17182/hepdata.68128

Characteristics of multi-particle production in proton-proton collisions at $\sqrt{s}$=7 TeV are studied as a function of the charged-particle multiplicity, $N_{ch}$. The produced particles are separated into two classes: those belonging to jets and those belonging to the underlying event. Charged particles are measured with pseudorapidity |η|<2.4 and transverse momentum $p_T$ > 0.25 GeV/c. Jets are reconstructed from charged-particles only and required to have $p_T$ > 5 GeV/c. The distributions of jet $p_T$, average $p_T$ of charged particles belonging to the underlying event or to jets, jet rates, and jet shapes are presented as functions of $N_{ch}$ and compared to the predictions of the PYTHIA and HERWIG event generators. Predictions without multi-parton interactions fail completely to describe the $N_{ch}$-dependence observed in the data. For increasing $N_{ch}$, PYTHIA systematically predicts higher jet rates and harder $p_T$ spectra than seen in the data, whereas HERWIG shows the opposite trends. At the highest multiplicity, the data–model agreement is worse for most observables, indicating the need for further tuning and/or new model ingredients.

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Underlying event characteristics and their dependence on jet size of charged-particle jet events in pp collisions at sqrt(s) = 7 TeV with the ATLAS detector

The ATLAS collaboration Aad, Georges ; Abbott, Brad ; Abdallah, Jalal ; et al.
Phys.Rev.D 86 (2012) 072004, 2012.
Inspire Record 1125575 DOI 10.17182/hepdata.58995

Distributions sensitive to the underlying event are studied in events containing one or more charged-particle jets produced in pp collisions at sqrt(s) = 7 TeV with the ATLAS detector at the Large Hadron Collider (LHC). These measurements reflect 800 inverse microbarns of data taken during 2010. Jets are reconstructed using the antikt algorithm with radius parameter R varying between 0.2 and 1.0. Distributions of the charged-particle multiplicity, the scalar sum of the transverse momentum of charged particles, and the average charged-particle pT are measured as functions of pT^JET in regions transverse to and opposite the leading jet for 4 GeV < pT^JET < 100 GeV. In addition, the R-dependence of the mean values of these observables is studied. In the transverse region, both the multiplicity and the scalar sum of the transverse momentum at fixed pT^JET vary significantly with R, while the average charged-particle transverse momentum has a minimal dependence on R. Predictions from several Monte Carlo tunes have been compared to the data; the predictions from Pythia 6, based on tunes that have been determined using LHC data, show reasonable agreement with the data, including the dependence on R. Comparisons with other generators indicate that additional tuning of soft-QCD parameters is necessary for these generators. The measurements presented here provide a testing ground for further development of the Monte Carlo models.

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