Transverse momentum distribution of primary charged particles in the p–Pb interactions using HIJING 1.0

2016 ◽  
Vol 31 (24) ◽  
pp. 1650136 ◽  
Author(s):  
U. Tabassam ◽  
Y. Ali ◽  
M. Suleymanov ◽  
A. S. Bhatti ◽  
J. B. Butt ◽  
...  

The shape of the transverse momentum [Formula: see text] distribution of primary charged particles in minimum bias (nonsingle-diffractive) p–Pb collisions at [Formula: see text] is studied in the pseudorapidity regions: [Formula: see text], [Formula: see text] and [Formula: see text] and in the transverse momentum range [Formula: see text] using simulated data produced with the HIJING 1.0 code. These are compared with the ALICE data measured by the ALICE detector at the LHC. In the model, the central and forward [Formula: see text]-regions differ more than in the ALICE data and due to this fact HIJING 1.0 cannot describe well the high [Formula: see text] region in the [Formula: see text] distributions. The comparison of results from simulation implies that the HIJING 1.0 considered narrower pseudorapidity distribution for the charged particles than it is in the ALICE data. It cannot take into account satisfactorily leading effect due to the asymmetric p–Pb fragmentation.

2020 ◽  
Vol 2020 ◽  
pp. 1-6
Author(s):  
Hai-Fu Zhao ◽  
Bao-Chun Li ◽  
Hong-Wei Dong

The distribution characteristic of final-state particles is one of the significant parts in high-energy nuclear collisions. The transverse momentum distribution of charged particles carries essential evolution information about the collision system. The Tsallis statistics is used to investigate the transverse momentum distribution of charged particles produced in Xe-Xe collisions at sNN=5.44 TeV. On this basis, we reproduce the nuclear modification factor of the charged particles. The calculated results agree approximately with the experimental data measured by the ALICE Collaboration.


Author(s):  
A. Arif ◽  
Y. Ali ◽  
M. Haseeb ◽  
Q. Ali ◽  
U. Tabassam ◽  
...  

We have studied transverse momentum distributions of charged particles produced in pp and Pb–Pb collisions at [Formula: see text] TeV and 5.02 TeV in the pseudorapidity interval [Formula: see text] and transverse momentum range [Formula: see text][Formula: see text]GeV/[Formula: see text]. We simulated data using EPOS-LHC, EPOS-1.99 and QGSJETII-04 models. The simulation data is compared with the ALICE experimental data values at [Formula: see text] TeV and 5.02 TeV for pp and most central Pb–Pb collisions. It has been observed that, EPOS-LHC and QGSJETII-04 models explain the experimental results for pp collision at [Formula: see text] TeV and 5.02 TeV. The behavior of nuclear modification factors has been studied. The simulation codes of all three models EPOS-LHC, EPOS-1.99 and QGSJETII-04 overestimate the experimental results at low transverse momentum interval: [Formula: see text] GeV/[Formula: see text], for Pb–Pb collisions at [Formula: see text] TeV and 5.02 TeV. However, only EPOS-LHC model can explain the experimental data at high transverse momentum in the range: [Formula: see text] GeV/[Formula: see text]. EPOS-1.99 and QGSJETII-04 underestimate in the region of Cronin effect and cannot give satisfactory estimates for the [Formula: see text] values for which [Formula: see text] demonstrates stronger suppression because of the collective parton effect. It can be inferred that these effects are not taken into account in EPOS-1.99 and QGSJETII-04 models. These models, however, satisfactorily explain the ALICE experimental data in the ranges of [Formula: see text] for which nuclear modification factor [Formula: see text] shows rising trend.


2007 ◽  
Vol 22 (15) ◽  
pp. 1105-1112
Author(s):  
L. L. ZHU ◽  
C. B. YANG

The transverse momentum distribution of charged particles is investigated for gold–gold collisions at [Formula: see text]. A simple parametrization is suggested for the particle distribution based on the nuclear stopping effect. The model can fit very well in both the transverse momentum distributions at different pseudo-rapidities and the pseudo-rapidity distributions at different centralities. The ratio of rapidity distributions for peripheral and central collisions is calculated and compared with the data.


Sign in / Sign up

Export Citation Format

Share Document