A detailed study of pseudorapidity densities and multiplicity distributions of primary charged particles produced in proton-proton collisions, at $\sqrt{s} =$ 0.9, 2.36, 2.76, 7 and 8 TeV, in the pseudorapidity range $|\eta|<2$, was carried out using the ALICE detector. Measurements were obtained for three event classes: inelastic, non-single diffractive and events with at least one charged particle in the pseudorapidity interval $|\eta|<1$. The use of an improved track-counting algorithm combined with ALICE's measurements of diffractive processes allows a higher precision compared to our previous publications. A KNO scaling study was performed in the pseudorapidity intervals $|\eta|<$ 0.5, 1.0 and 1.5. The data are compared to other experimental results and to models as implemented in Monte Carlo event generators PHOJET and recent tunes of PYTHIA6, PYTHIA8 and EPOS.
This note describes the details of the analysis of charged-particle pseudorapidity densities and multiplicity distributions measured by the ALICE detector in pp collisions at $\sqrt{s}$ = 0.9 and 7 TeV in specific phase space regions. The primary goal of the analysis is to provide reference measurements for Monte Carlo tuning. The pseudorapidity range |h| < 0.8 is considered and a lower $p_T$ cut is applied, at 0.15, 0.5 GeV/c and at 1 GeV/c. The choice of such phase space regions to measure the charged-particle multiplicity allows a direct comparison with the analogous results obtained by other LHC collaborations, namely ATLAS and CMS. The class of events considered are those having at least one charged particle in the kinematical ranges just described. In the note, the analysis procedure is presented, together with the corrections applied to the data, and the systematic uncertainty evaluation. The comparison of the results with different Monte Carlo generators is also shown.
The multiplicity and pseudorapidity distributions of inclusive photons have been measured at forward rapidities ($2.3 < \eta < 3.9$) in proton-proton collisions at three center-of-mass energies, $\sqrt{s}=0.9$, 2.76 and 7 TeV using the ALICE detector. It is observed that the increase in the average photon multiplicity as a function of beam energy is compatible with both a logarithmic and a power-law dependence. The relative increase in average photon multiplicity produced in inelastic pp collisions at 2.76 and 7 TeV center-of-mass energies with respect to 0.9 TeV are 37.2% $\pm$ 0.3% (stat) $\pm$ 8.8% (sys) and 61.2% $\pm$ 0.3% (stat) $\pm$ 7.6% (sys), respectively. The photon multiplicity distributions for all center-of-mass energies are well described by negative binomial distributions. The multiplicity distributions are also presented in terms of KNO variables. The results are compared to model predictions, which are found in general to underestimate the data at large photon multiplicities, in particular at the highest center-of-mass energy. Limiting fragmentation behavior of photons has been explored with the data, but is not observed in the measured pseudorapidity range.
Multiplicity ($N_{\rm ch}$) distributions and transverse momentum ($p_{\rm T}$) spectra of inclusive primary charged particles in the kinematic range of $|\eta| < 0.8$ and 0.15 GeV/$c$$< p_{T} <$ 10 GeV/$c$ are reported for pp, p-Pb, Xe-Xe and Pb-Pb collisions at centre-of-mass energies per nucleon pair ranging from $\sqrt{s_{\rm NN}} = 2.76$ TeV up to $13$ TeV. A sequential two-dimensional unfolding procedure is used to extract the correlation between the transverse momentum of primary charged particles and the charged-particle multiplicity of the corresponding collision. This correlation sharply characterises important features of the final state of a collision and, therefore, can be used as a stringent test of theoretical models. The multiplicity distributions as well as the mean and standard deviation derived from the $p_{\rm T}$ spectra are compared to state-of-the-art model predictions. Providing these fundamental observables of bulk particle production consistently across a wide range of collision energies and system sizes can serve as an important input for tuning Monte Carlo event generators.
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