Understanding The Jet Activities In Association With The Dileptons Using Machine Learning Techniques With The Use Of The ATLAS Detector At LHC

Researcher: Mashaka Molepo, University of Venda
Supervisor: Professor Bruce Mellado, University of the Witwatersrand, Johannesburg

The use of neural networks as sources for the study in Monte Carlo simulation for the detection of hadronic -decay w boson including strong jet quacks [1]. The need for data science algorithms in deep neural networks leads to a strong rejection of the fundamental one-jet correlation sub-structure [1]. The use of deep learning methods has been noticed in the context of an increased deep neural networks to enhance context exclusion including the use of implantation sub-sub-structures and mass-tagers [1]. The corresponding classifiers are often linearly associated with the parameters in their substructures.