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TokaMind model advances tokamak plasma dynamics research

Researchers have introduced TokaMind, an open-source foundation model designed for tokamak plasma dynamics. This model utilizes a Multi-Modal Transformer architecture and has been pre-trained on diverse data from the MAST dataset, including time-series, 2D profiles, and videos. TokaMind demonstrates strong performance on various reconstruction and forecasting tasks, outperforming existing benchmarks and highlighting the benefits of multi-modal pre-training for fusion modeling. AI

IMPACT Provides a foundational, adaptable model for complex fusion energy simulations, potentially accelerating research.

RANK_REASON The cluster contains an academic paper detailing a new model and its evaluation on a benchmark. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Tobia Boschi, Andrea Loreti, Nicola C. Amorisco, Rodrigo H. Ordonez-Hurtado, C\'ecile Rousseau, George K. Holt, Eszter Sz\'ekely, Alexander Whittle, Samuel Jackson, Adriano Agnello, Stanislas Pamela, Alessandra Pascale, Robert Akers, Juan Bernabe Moreno,… ·

    TokaMind: A Multi-Modal Transformer Foundation Model for Tokamak Plasma Dynamics

    arXiv:2602.15084v2 Announce Type: replace-cross Abstract: 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 MAS…