Speaker
Description
Partial Wave Analysis (PWA) provides us with a richer understanding of particle scattering phenomena than, for example, cross sections. PWA has been employed for decades in nuclear physics data, but there are several considerable hurdles that make this topic a challenging one, including large parameter spaces and multiple solutions. In this talk, I will present some of the work done within our group, whose focus is applying AI techniques to PWA. Utilizing autoencoders to study nuclear/particle physics reactions has proven beneficial in better understanding these partial waves. I will discuss promising results already achieved by this group, as well as inherent challenges that we’re still facing.