Probabilistic and Geometry Aware Neural Surrogate of Scrape Off Layer Plasma Simulations

arXiv:2609.28116 · cs.LG, physics.plasm-ph · Submitted 2026-09-23 · Read on arXiv

cs.LG, physics.plasm-ph

Submitted: 2026-09-23

Updated: 2026-09-23

Terminology

• Core — 6× in this paper · explained in 2 episodes
• Flow Matching — 4× in this paper · explained in 8 episodes
• Fidelity — 3× in this paper · explained in 2 episodes
• Accuracy — 2× in this paper · explained in 1 episode
• Diffusion Model — 2× in this paper · explained in 8 episodes
• Diffusion Models — 2× in this paper · explained in 6 episodes
• In International Conference on Learning Representations — 2× in this paper
• Verification — 2× in this paper · explained in 2 episodes
• Adam — 1× in this paper · explained in 2 episodes
• Generative Modeling — 1× in this paper · explained in 3 episodes
• Neural Surrogates — 1× in this paper · explained in 2 episodes
• Rectified Flow — 1× in this paper · explained in 3 episodes
• Regularization — 1× in this paper · explained in 3 episodes

Sources

• Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning
• Deep-Learning based surrogate models for plasma exhaust simulations -- SOLPS-NN
• Flow Matching for Generative Modeling
• Flow Matching Guide and Code
• Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow

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