3 papers
hep-th2025
Physics-informed neural network solves minimal surfaces in curved spacetime
Koji Hashimoto, Koichi Kyo, Masaki Murata +2
We develop a flexible framework based on physics-informed neural networks (PINNs) for solving boundary value problems involving minimal surfaces in curved spacetimes, with a partic…
hep-th2024
Machine-learning emergent spacetime from linear response in future tabletop quantum gravity experiments
Koji Hashimoto, Koshiro Matsuo, Masaki Murata +2
We introduce a novel interpretable Neural Network (NN) model designed to perform precision bulk reconstruction under the AdS/CFT correspondence. According to the correspondence, a…
hep-th2024
Comparative Study of Neural Network Methods for Solving Topological Solitons
Koji Hashimoto, Koshiro Matsuo, Masaki Murata +1
Topological solitons, which are stable, localized solutions of nonlinear differential equations, are crucial in various fields of physics and mathematics, including particle physic…