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cs.AI2026
Physics-Informed Neural Networks for Complex Eigenfrequency Identification and Mode Structure Reconstruction of the Ground-State ITG Branch
Dengdi Sun, Bingbing Zhang, Xiao Wang +5
Physics-informed neural networks (PINNs) combine sparse observations with physical equations, providing an important approach for modeling complex plasma processes and inferring un…
cs.CV2026
Visible-Light Imaging Diagnosis of Neutral Particle Emission Tomography in the Tokamak Divertor: An Efficient Transformer-based Surrogate Model
Xiao Wang, Hao Si, Qiang Chen +8
Nuclear fusion has made significant progress in recent years and is expected to become one of the most important pathways to addressing global energy challenges. This paper focuses…
cs.CV2026
Hierarchical Multi-to-Single-Modal Knowledge Distillation for Disruption Prediction in EAST
Qiang Chen, Xiao Wang, Hao Si +9
Plasma disruption is a critical threat to tokamak safety. Existing data-driven predictors mainly rely on time-series diagnostic signals, while visible images provide complementary…