Mahmoud Y. El-Bakry

GENETIC PROGRAMING MODELING FOR NUCLEUS–NUCLEUS COLLISIONS

High Energy Physics (HEP), due to the vast and complex data expected from current and future experiments, is in need of powerful and efficient techniques for various analysis tasks. Genetic Programing (GP) is a powerful technique that can be used such complex tasks. In this paper, Genetic programing is used for modeling the functions that describe the pseudo-rapidity distribution of the shower particles for 12C, 16O, 28Si and 32S on nuclear emulsion and also to predict the distributions that are not present in the training set and matched them effectively. The proposed method shows a better fitting with experimental data. The GP prediction results prove a strong presence modeling in heavy ion collisions.

Artificial Neural Network And Genetic Algorithm Hybrid Technique For Nucleus–Nucleus Collisions

Selecting the optimal topology of a neural network for a particular application is a difficult task. Genetic Algorithm (GA) has been used to find the optimal neural network (NN) solution (i.e., hybrid technique) to calculate the pseudo-rapidity distribution of the shower particles for C12, O16, Si28, and S32 on nuclear emulsion. An efficient NN has been designed by GA to predict the distributions that are not present in the training set and matched them effectively. The proposed method shows a better fitting with experimental data. The hybrid technique GA–ANN simulation results prove a strong presence modeling in heavy ion collisions.

Modeling of Transverse Momentum Spectra for Charged Particles in Proton–Proton Collisions Based on Soft Computing Approaches

ABSTRACT The transverse momentum (pT) distributions (or spectra) of charged particles produced in high and ultra-high energy proton–proton (pp) collisions are studied by the neuro-fuzzy model. The objective of the present work is developing an Adaptive Neuro-Fuzzy Inference System (ANFIS) for calculating and predicting the transverse momentum spectra of charged particles as a function of pT and the center-of-mass energy (), as well as the modeling of the average transverse momentum ⟨pT⟩ as a function of , i.e., we have proposed and developed two models. The ANFIS models were designed based on available experimental data for = 53 GeV, 200 GeV, 546 GeV, 900 GeV, 1800 GeV, 2360 GeV and 7 TeV. The empirical results from the developed ANFIS models for pT distributions, as well as ⟨pT⟩ for pp collisions are compared with the theoretical ones which are obtained from other models. The comparison results show a great deal of agreement between the available experimental data (up to 7 TeV) and the theoretical ones. At full large hadron collider (LHC) energy ( = 14 TeV), we have predicted the pT spectra and ⟨pT⟩ which also, show a good agreement with different models.