Seminarium Fizyki Wielkich Energii

In this talk, I will explore how concepts from information geometry can provide new insights into complex phenomena in high-energy physics. I will present two illustrative examples: (1) a product manifold approach in machine learning that enhances classification performance for Vector Boson Fusion decays, and (2) a reformulation of CP violation from an information-geometric perspective. Finally, I will discuss potential applications of these techniques in the upcoming Phase-2 upgrade of the CMS experiment.