Quantum Machine Learning concepts and applications

We explore Machine Learning techniques and Quantum Computing concepts that could be applied in High Energy Physics considering a phenomenological and theoretical view. In this framework, we show the main tools to explore the Standard Model extensions, decay process and the parameter space. With this set of tools, we want to explore the bounds and define exclusion regions, this results might be interesting for the next generation of colliders and could prove to be useful in the understanding of phenomena.