Generative adversarial networks (GANs) are essentially a min-max game between the discriminator and a generator. Coulomb GANs have a closely related formulation where the generator minimizes the potential difference between real (negative) and fake (positive) charge densities, wherein the discriminator approximates a low-dimensional Plummer kernel centered around the samples. Motivated by links between electrostatic potential theory and the Poisson partial differential equation (PDE), we conside…