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physics.plasm-ph2026
The Fusion Equilibrium Challenge: Inferring Magnetic Geometry Without Magnetic Diagnostics
Tapan Ganatma Nakkina, Matthew Waller, Craig Michoski +6
Next-generation fusion reactor devices such as SPARC, ARC, and CFETR will operate in extreme neutron environments that compromise the magnetic sensors traditionally used to reconst…
physics.plasm-ph2025
The Data Fusion Labeler (dFL): Challenges and Solutions to Data Harmonization, Labeling, and Provenance in Fusion Energy
Craig Michoski, Matthew Waller, Brian Sammuli +14
Fusion energy research increasingly depends on the ability to integrate heterogeneous, multimodal datasets from high-resolution diagnostics, control systems, and multiscale simulat…
physics.plasm-ph2025
TGLF-WINN: Data-Efficient Deep Learning Surrogate for Turbulent Transport Modeling in Fusion
Yadi Cao, Futian Zhang, Wesley Liu +7
The Trapped Gyro-Landau Fluid (TGLF) model provides fast, accurate predictions of turbulent transport in tokamaks, but whole device simulations requiring thousands of evaluations r…