Charged Particle Pseudorapidity Distributions for Pb–Pb and Au–Au Collisions using Neural Network Model

  • M. Y. El-Bakry Department of Physics, Faculty of Education, Ain Shams University, Buraydah Tabouk University, Faculty of Science, Department of Physics
  • El-Sayed A. El-Dahshan Dept. of Phys., Faculty of Science, Ain Shams University, Egyptian E-Learning University
  • E. F. Abd El-Hamied Department of Physics, Faculty of Education, Ain Shams University
Keywords: charged particles, neural network, pseudorapidity distribution, Pb–Pb and Au–Au collisions, simulation

Abstract

The artificial neural network (ANN) approach is used to model the Pb–Pb and Au–Au collisions on the basis of the Levenberg–Marquardt learning algorithm. We simulate the rapidity distribution for п- and к+- produced in Pb–Pb collisions at different energies and the pseudorapidity distribution of charged particles in Au–Au collisions. Our functions obtained within the ANN model show a very good agreement with the experimental data for both types of collisions, which indicates that the trained network takes on the optimal generalization performance. Thus, the ANN model can be widely applied to the modeling of heavy-ion collisions.

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Published
2018-10-10
How to Cite
El-Bakry, M., El-Dahshan, E.-S., & Abd El-Hamied, E. (2018). Charged Particle Pseudorapidity Distributions for Pb–Pb and Au–Au Collisions using Neural Network Model. Ukrainian Journal of Physics, 58(8), 709. https://doi.org/10.15407/ujpe58.08.0709
Section
Nuclei and nuclear reactions