International Journal of Modern Physics C · 2009 · 19 citations · 8 references
Natural SciencesPhysicsNuclear ChemistryNuclear PhysicsParticle PhysicsCollider PhysicsGenetic ProgrammingHeavy-ion PhysicsNuclear ModelsInterpreting Experimental DataIon-ion CollisionsRelativistic Heavy-ion 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 12 C , 16 O , 28 Si and 32 S 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.
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