Diffusion Modeling of the Solar Corona

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Diffusion models such as DeepMind's GenCast have demonstrated powerful performance in terrestrial weather forecasting, achieving results on-par and surpassing leading medium-range numerical weather simulations. We present our initial results to train a Denoising Diffusion Probabilistic Model (DDPM) of the solar corona, aimed as a first step at generating synthetic solar magnetic fields based on conditioning inputs. Conditioning inputs include multi-spectral imagery, magnetograms, and other measurements commonly used to frame coronal inverse problems....