Measurements are presented from proton-proton collisions at centre-of-mass energies of sqrt(s) = 0.9, 2.36 and 7 TeV recorded with the ATLAS detector at the LHC. Events were collected using a single-arm minimum-bias trigger. The charged-particle multiplicity, its dependence on transverse momentum and pseudorapidity and the relationship between the mean transverse momentum and charged-particle multiplicity are measured. Measurements in different regions of phase-space are shown, providing diffraction-reduced measurements as well as more inclusive ones. The observed distributions are corrected to well-defined phase-space regions, using model-independent corrections. The results are compared to each other and to various Monte Carlo models, including a new AMBT1 PYTHIA 6 tune. In all the kinematic regions considered, the particle multiplicities are higher than predicted by the Monte Carlo models. The central charged-particle multiplicity per event and unit of pseudorapidity, for tracks with pT >100 MeV, is measured to be 3.483 +- 0.009 (stat) +- 0.106 (syst) at sqrt(s) = 0.9 TeV and 5.630 +- 0.003 (stat) +- 0.169 (syst) at sqrt(s) = 7 TeV.
A measurement of the underlying event (UE) activity in proton-proton collisions at a center-of-mass energy of 7 TeV is performed using Drell--Yan events in a data sample corresponding to an integrated luminosity of 2.2 inverse femtobarns, collected by the CMS experiment at the LHC. The activity measured in the muonic final state (q q-bar to opposite-sign muons) is corrected to the particle level and compared with the predictions of various Monte Carlo generators and hadronization models. The dependence of the UE activity on the dimuon invariant mass is well described by PYTHIA and HERWIG++ tunes derived from the leading jet/track approach, illustrating the universality of the UE activity. The UE activity is observed to be independent of the dimuon invariant mass in the region above 40 GeV, while a slow increase is observed with increasing transverse momentum of the dimuon system. The dependence of the UE activity on the transverse momentum of the dimuon system is accurately described by MADGRAPH, which simulates multiple hard emissions.
A measurement of the underlying activity in scattering processes with a hard scale in the several GeV region is performed in proton-proton collisions at sqrt(s) = 0.9 and 7 TeV, using data collected by the CMS experiment at the LHC. The production of charged particles with pseudorapidity |eta| < 2 and transverse momentum pT > 0.5 GeV/c is studied in the azimuthal region transverse to that of the leading set of charged particles forming a track-jet. A significant growth of the average multiplicity and scalar-pT sum of the particles in the transverse region is observed with increasing pT of the leading track-jet, followed by a much slower rise above a few GeV/c. For track-jet pT larger than a few GeV/c, the activity in the transverse region is approximately doubled with a centre-of-mass energy increase from 0.9 to 7 TeV. Predictions of several QCD-inspired models as implemented in PYTHIA are compared to the data.
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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