Real-time virtual circuits for plasma shape control via neural network emulators: integration and testing in the MAST-U PCS

arXiv:2608.26216 · physics.plasm-ph, cs.LG · Submitted 2026-08-26 · Read on arXiv

physics.plasm-ph, cs.LG

Submitted: 2026-08-26

Updated: 2026-08-26

Code: https://github.com/Tencent/ncnn

Terminology

• Accuracy — 5× in this paper · explained in 1 episode
• Core — 4× in this paper · explained in 2 episodes
• Reinforcement Learning — 3× in this paper · explained in 4 episodes
• Calibration — 2× in this paper · explained in 7 episodes
• Deep Reinforcement Learning — 2× in this paper · explained in 2 episodes
• Adam — 1× in this paper · explained in 2 episodes
• Adaptivity — 1× in this paper · explained in 1 episode
• Communication Overhead — 1× in this paper · explained in 2 episodes
• FreeGSNKE Pulse Design Tool — 1× in this paper
• Robustness — 1× in this paper · explained in 5 episodes
• Verification — 1× in this paper · explained in 2 episodes

Sources

• Real-time virtual circuits for plasma shape control via neural network emulators: dynamic validation in closed-loop simulations
• The FreeGSNKE Pulse Design Tool (FPDT): a computational framework for evolutive plasma scenario and control design

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