Speaker
Haruto Kitagawa
Description
In this talk, we present a model-independent analysis based on a latent diffusion model to address the flavor structure of leptons. The latent diffusion model combines a diffusion model with a variational autoencoder as a generative AI framework. By generating a wide variety of parameter sets consistent with experimental observations, we find non-trivial features characterizing lepton flavor structures.
