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This paper introduces the first systematic robustness benchmark for plasma diagnostic machine learning models using the TokaMark dataset, evaluating architectures across six sensor failure scenarios and introducing a Robustness Score for cross-architecture comparison.
Commonwealth Fusion Systems has published five peer-reviewed papers detailing the physics basis for its ARC fusion power plant, which is expected to produce 400 MW of electricity. The company's approach uses high-temperature superconductors to build a smaller, faster reactor.
This paper introduces RL4F, an offline reinforcement learning benchmark for plasma control in nuclear fusion, providing closed-loop evaluation environments and baseline comparisons across four profile tracking tasks using real tokamak data from DIII-D. The codebase and datasets are open-sourced to foster further research.