AI for QFT

2 PM, 27 Mar 2025

In two consecutive talks, Prof. Koji Hashimoto and Dr Akio Tomiya discuss applying machine learning to problems in quantum field theory.

Two seminars discuss new applications of AI to quantum theory. Prof. Koji Hashimoto of Kyoto University shows how a neural network can generate arbitrary Feynman path integrals as a consequence of the universal approximation theorem. Afterwards, Dr Akio Tomiya of Tokyo Woman's Christian University introduces a transformer architecture designed for lattice QCD that outperforms existing gauge covariant neural networks.

AI for QFT
AI for QFT
AI for QFT
AI for QFT
AI for QFT
AI for QFT
AI for QFT
AI for QFT
AI for QFT
AI for QFT
AI for QFT
AI for QFT
AI for QFT
AI for QFT
AI for QFT
AI for QFT