Speaker
Description
Exclusive reactions measured at the intensity frontier open new opportunities to study QCD. Processes in a multi-dimensional phase space require adequate tools to take advantage of correlations between variables that embed the underlying strong-force interaction. To extend our capability of interpreting multi-dimensional data and fully reconstruct correlations between final state particles, we propose a new approach that uses AI-based algorithms trained on real data to unfold detector effects and reveal the interaction mechanisms at the vertex level. The A(i)DAPT project is a collaborative effort between experimental and theoretical physicists and data scientists to develop new methods of extracting the underlying physics with state-of-the-art machine learning techniques, such as generative adversarial networks. In this contribution, I will present the project and some selected results obtained in inclusive and exclusive electron and photon scattering from protons.
