arXiv: cs.AI preprintsInternational6 November 2026
A Generative Foundation Model for Multimodal Tokamak Tasks
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arXiv:2611.08153v1 Announce Type: new Abstract: Tokamak experiments record diverse measurements, including waveforms, profiles, fields, and scalars, which are used to reconstruct the plasma, forecast its evolution, recover associated control signals, and estimate disruption risk. Most models are built separately for one task and a fixed set of inputs and outputs, and each relies on a prescribed subset of diagnostics rather than structuring the full multimodal observation set to extract global, cross-signal information about the discharge. These limitations motivate a reusable foundation model
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