SOURCE-LINKED INTELLIGENCE
Probabilistic and Geometry Aware Neural Surrogate of Scrape Off Layer Plasma Simulations
Fast surrogates for tokamak boundary-plasma simulation are typically deterministic regressors mapping a global operating point to a flattened vector of cell values. Near the divertor detachment transition the steady state is not reliably single-valued. A point estimate must average over qualitatively different plasma states, and it arrives with no statement of confidence. Moreover, the flattened vector representation discards the geometric structure of the SOLPS-ITER mesh. This work addresses both problems. We unroll the curvilinear mesh into three fixed-size image tensors whose layout preserv
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-23T13:45:19.000Z
First collected: 2026-09-24T08:22:30.429Z. This is not the publication date.