10 citations · 14 across the 6 of their papers we have counts for
5 papers · 1 filter
Uncovering Hidden Leptonic Correlations with Flow Matching and Autoencoders
Haruto Kitagawa, Satsuki Nishimura, Hajime Otsuka
We perform a global search for values of the Yukawa matrices and Majorana masses in the Type-I seesaw mechanism. Using flow matching, which is a generative artificial intelligence…
Revisiting One-Zero and Two-Zero Neutrino Mass Textures in Light of Recent Oscillation and Cosmological Data
Haruto Kitagawa, Coh Miyao, Satsuki Nishimura +1
We revisit one-zero and two-zero textures of the neutrino mass matrix under current experimental and cosmological constraints. We identify the phenomenologically viable texture str…
Diffusion-model approach to flavor models: A case study for modular flavor model
Satsuki Nishimura, Hajime Otsuka, Haruki Uchiyama
We propose a numerical method of searching for parameters with experimental constraints in generic flavor models by utilizing diffusion models, which are classified as a type of ge…
Exploring the flavor structure of leptons via diffusion models
Satsuki Nishimura, Hajime Otsuka, Haruki Uchiyama
We propose a method to explore the flavor structure of leptons using diffusion models, which are known as one of generative artificial intelligence (generative AI). We consider a s…
Reinforcement learning-based statistical search strategy for an axion model from flavor
Satsuki Nishimura, Coh Miyao, Hajime Otsuka
We propose a reinforcement learning-based search strategy to explore new physics beyond the Standard Model. The reinforcement learning, which is one of machine learning methods, is…