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.
Jet shapes have been measured in inclusive jet production in proton-proton collisions at sqrt(s) = 7 TeV using 3 pb^{-1} of data recorded by the ATLAS experiment at the LHC. Jets are reconstructed using the anti-kt algorithm with transverse momentum 30 GeV < pT < 600 GeV and rapidity in the region |y| < 2.8. The data are corrected for detector effects and compared to several leading-order QCD matrix elements plus parton shower Monte Carlo predictions, including different sets of parameters tuned to model fragmentation processes and underlying event contributions in the final state. The measured jets become narrower with increasing jet transverse momentum and the jet shapes present a moderate jet rapidity dependence. Within QCD, the data test a variety of perturbative and non-perturbative effects. In particular, the data show sensitivity to the details of the parton shower, fragmentation, and underlying event models in the Monte Carlo generators. For an appropriate choice of the parameters used in these models, the data are well described.
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