The big this seems to be that their noising/denoising process is invertible (to some extent) so it can be used to generate uncertainties, which is something the article says diffusion models can't do. The intuition is that the "flow" process used here is reversible (imagine going backwards in time and watching a cloud of charged particles coalescing into a bunch), which gives some nice properties that random blurring used in more common diffusion models does not.

I think it's the reversible flow part that's important for the results, not the connection to the physical electrostatics system. It just happens to be that electrostatics have this nice flow behavior too and are a pretty approachable analogy for what the model's doing.