Conditional Denoising Model as a Physical Surrogate Model

This paper explores the use of conditional denoising models as physical surrogate models for complex physical systems. It addresses the common trade-off between data-fitting accuracy and physical consistency in surrogate modeling. This approach has potential for accurately simulating physical phenomena, particularly in fields like plasma physics.