Login / Signup

Charged Particles Transverse Momentum and Pseudorapidity Distribution in Hadronic Collisions at LHC Energies.

Muhammad AjazAbd Al Karim Haj IsmailMateen Ullah MianRashid KhanRamoona ShehzadiMuhammad Adil KhanAtef AbdelKaderMuhammad WaqasElmuez A DawiUzma Tabassam
Published in: Entropy (Basel, Switzerland) (2023)
We present an analysis of the pseudorapidity η and transverse momentum pT distributions of charged hadrons in pp collisions for the kinematic range of 0<pT<4 GeV/c and |η|<2.4 at 0.9, 2.36, and 7 TeV. Charged particles are produced in pp collision using several Monte Carlo event generators (Pythia Simple, Vincia, Dire showers, Sibyll2.3d, QGSJETII-04, EPOS-LHC) and compared with CMS data at LHC. It is observed that the Simple parton showers can explain the CMS data very well for pT>1 GeV/c at 0.9 and 2.36 TeV within the experimental errors, while Dire overshoots and Vicia undershoots the data by 50% each. At 7 TeV, the Dire module presents a good prediction, whereas the Simple and Vincia modules underestimate the data within 30% and 50%. Comparing the Simple module of the Pythia model and the predictions of the CRMC models with the experimental data shows that at 0.9 TeV, EPOS-LHC has better results than the others. At 2.36 GeV, the cosmic rays Monte Carlo (CRMC) models have better prediction than the Simple module of Pythia at low pT, while QGSJETII-04 predicts well at high pT. QGSJETII-04 and EPOS-LHC have closer results than the Pythia-Simple and Sibyll2.3d at 7 TeV. In the case of the pseudorapidity distributions, only the Pythia-Simple reproduced the experimental measurements at all energies. The Dire module overestimates, while Vincia underestimates the data in decreasing order of discrepancy (20%, 12%, 5%) with energy. All CRMC models underestimate the data over the entire η range at all energies by 20%. The angular ordering of partons and the parton fragmentation could be possible reasons for this deviation. Furthermore, we used the two-component standard distribution to fit the pT spectra to the experimental data and extracted the effective temperature (Teff) and the multiplicity parameter (N0). It is observed that Teff increases with the increase in the center of mass energy. The fit yielded 0.20368±0.01, 0.22348±0.011, and 0.24128±0.012 GeV for 0.9, 2.36, and 7 TeV, respectively. This shows that the system at higher energies freezes out earlier than lower ones because they quickly attain the equilibrium state.
Keyphrases
  • electronic health record
  • monte carlo
  • big data
  • data analysis
  • adverse drug
  • molecular dynamics simulations