TokaMind: A Multi-Modal Transformer Foundation Model for Tokamak Plasma Dynamics
We present TokaMind, to our knowledge the first open-source foundation model for tokamak plasma dynamics, based on a Multi-Modal Transformer (MMT) and pretrained on heterogeneous diagnostics from the publicly available MAST dataset. TokaMind supports multiple data modalities (time-series, 2D profiles, and videos) with different sampling rates, robust missing-signal handling, and efficient task adaptation via selectively loading and freezing four model components. To represent multi-modal signals, we use a lightweight fixed-basis Discrete Cosine Transform embedding (DCT3D) and provide a clean interface for alternative embeddings (e.g., Variational Autoencoders). We evaluate TokaMind on the...
| Authors | Tobia Boschi, Andrea Loreti, Nicola C. Amorisco et al. |
|---|---|
| Primary category | physics.plasm-ph |
| Published | 16 February 2026 |
| Last updated at source | 5 June 2026 |
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