Physics-Informed Neural Operator Surrogate for 2D Magnetohydrodynamic Reconnection

arXiv:2609.29514 · physics.plasm-ph, stat.ML · Submitted 2026-08-25 · Read on arXiv

physics.plasm-ph, stat.ML

Submitted: 2026-08-25

Updated: 2026-08-25

Terminology

• Accuracy — 6× in this paper · explained in 1 episode
• Fourier Neural Operator — 6× in this paper
• Consistency — 4× in this paper · explained in 3 episodes
• Ablation — 3× in this paper · explained in 1 episode
• Self-consistency — 3× in this paper · explained in 2 episodes
• Fidelity — 2× in this paper · explained in 2 episodes
• Activation Function — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• Core — 1× in this paper · explained in 2 episodes
• Initial Data — 1× in this paper · explained in 2 episodes
• Structural Constraints — 1× in this paper · explained in 2 episodes

Sources

• Neural Operator: Graph Kernel Network for Partial Differential Equations
• Neural Operator: Learning Maps Between Function Spaces
• Fourier Neural Operator with Learned Deformations for PDEs on General Geometries
• Physics-Informed Neural Operator for Learning Partial Differential Equations
• Towards Stability of Autoregressive Neural Operators
• Fourier Neural Operator for Parametric Partial Differential Equations
• Gaussian Error Linear Units (GELUs)

Related papers

• Is Your AI Fast Enough to Run a Fusion Reactor?
• GyroSwin: 5D Surrogates for Gyrokinetic Plasma Turbulence Simulations
• Electromagnetic ghosts in pair plasmas
• Collisionless whistler heat-flux instability in ultra-high- beta plasmas
• Rugged magneto-hydrodynamic invariants in weakly collisional plasma turbulence: Two-dimensional hybrid simulation results
• Hybrid Fourier Neural Operator-Plasma Fluid Model for Fast and Accurate Multiscale Simulations of High Power Microwave Breakdown