Physics Attention Transformer Surrogate for Rapid Vertical Instability Growth Rate Prediction: Alcator C-Mod to SPARC

arXiv:2608.24785 · physics.plasm-ph, math-ph, math.MP, stat.ML · Submitted 2026-08-25 · Read on arXiv

physics.plasm-ph, math-ph, math.MP, stat.ML

Submitted: 2026-08-25

Updated: 2026-08-25

Terminology

• Core — 11× in this paper · explained in 2 episodes
• Fidelity — 10× in this paper · explained in 2 episodes
• Benchmark — 7× in this paper · explained in 2 episodes
• Double Null — 7× in this paper
• Embeddings — 7× in this paper · explained in 2 episodes
• Accuracy — 6× in this paper · explained in 1 episode
• Transformer — 6× in this paper · explained in 2 episodes
• Calibration — 5× in this paper · explained in 7 episodes
• DeepONet — 5× in this paper · explained in 2 episodes
• Physics Attention Transformer — 5× in this paper
• Consistency — 4× in this paper · explained in 3 episodes
• Fourier Neural Operator — 4× in this paper
• Generalization — 4× in this paper · explained in 13 episodes
• Benchmarking — 3× in this paper · explained in 4 episodes
• Epistemic Uncertainty — 3× in this paper · explained in 10 episodes
• Tokenization — 3× in this paper · explained in 2 episodes
• Ablation — 2× in this paper · explained in 1 episode
• AUC — 1× in this paper · explained in 2 episodes
• AUROC — 1× in this paper · explained in 2 episodes
• Adam — 1× in this paper · explained in 2 episodes
• Aggregation — 1× in this paper · explained in 1 episode
• Deferral — 1× in this paper · explained in 2 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Latent Space — 1× in this paper · explained in 7 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• SPARC Synthetic Library — 1× in this paper
• Temporal consistency — 1× in this paper · explained in 2 episodes
• Uncertainty Quantification — 1× in this paper · explained in 8 episodes

Sources

• FGE: A Fast Free-Boundary Grad-Shafranov Evolutive Solver
• Fourier Neural Operator for Parametric Partial Differential Equations
• Fourier Neural Operator with Learned Deformations for PDEs on General Geometries
• SGDR: Stochastic Gradient Descent with Warm Restarts
• Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles

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