A GPU-accelerated implicit solver for electromagnetic field computations in full 3D tokamak simulations, featuring co-designed hierarchical domain decomposition and fast exact local solver for efficient large-scale parallel GPU computing.
See LICENSE fileTokamakElectromagnetic SimulationGPU Acceleration
A physics-informed neural operator learns the map between function spaces in magnetohydrodynamic simulations, enabling efficient state inference for magnetic reconnection at any parameter and time step, significantly reducing computational cost at high Lundquist numbers.
See LICENSE fileMagnetohydrodynamicsMagnetic ReconnectionNeural Operator
Proposes a KAN-based single-parameterized surrogate model to accelerate drift kinetic equation solving for fast neoclassical toroidal viscosity torque calculation in tokamak plasma modeling.
See LICENSE fileTokamakPlasma PhysicsDrift Kinetic
