Determination of Proton–Proton Interaction at Large Hadrons | Chapter 6 | Current Perspective to Physical Science Research Vol. 6

This paper describes how to use Genetic Programming (GP) as an evolutionary computational that is a family of algorithms for global optimization. The GP is an algorithm used for global optimisation in particle physics [1]. The GP is based on Darwin’s evolutionary theory of nature. GP, as a global optimization technique used by discovery of a new function for modeling physical phenomena. The p-p interactions are modeled at Large Hadron Collider (LHC) experiments, the number of charged particles multiplicity <n> and the total cross-section, σT as functions of the total center of mass energy (from low to ultra-high energy), √8 are discovered by using GP. In view of the discovered function for <n> √8 , the overall trend of the values predicted is consistent with LHC data [predicted values are 34.8638 and 35.3520 at √8 = 13 TeV and √8 14 TeV respectively]. The new function σT √8 , trained on experimental data of Particle Data Group (PDG) demonstrates a nice match to the other models. The predicted values of the total cross section at √8 = 13 TeV, and 14 TeV are found to be 109.0381 mb and 111.8329 mb respectively. Furthermore, the values predicted are agreed with other models like Block. Furthermore, the values predicted are agreed with other models like Block. To conclude, in high-energy physics GP has become one of the leading study fields.

Author(s) Details:

Amr Radi,
Department of Physics, College of Sciences, Sultan Qaboos University, Al Khoudh, Muscat 123, Oman and Department of Physics, Faculty of Sciences, Ain Shams University, Egypt.

Please see the link here: https://stm.bookpi.org/CPPSR-V6/article/view/13252