2 papers
physics.flu-dyn2026
Achieving angular-momentum conservation with physics-informed neural networks in computational relativistic spin hydrodynamics
Hidefumi Matsuda, Koichi Hattori, Koichi Murase
We propose physics-informed neural networks (PINNs) as a numerical solver for relativistic spin hydrodynamics and demonstrate that the total angular momentum, i.e., the sum of orbi…
hep-ph2026
Physics-informed neural networks for angular-momentum conservation in computational relativistic spin hydrodynamics
Hidefumi Matsuda, Koichi Hattori, Koichi Murase
Theoretical developments in relativistic spin hydrodynamics, which describes the macroscopic transport of spin angular momentum alongside other fundamental conserved quantities, ha…