A blob method for diffusion
Jos\'e Antonio Carrillo, Katy Craig, Francesco S. Patacchini

TL;DR
This paper introduces a deterministic particle method inspired by vortex blob techniques for simulating diffusion processes, ensuring particles remain particles and accurately capturing various diffusive PDEs.
Contribution
It develops a novel regularization-based blob method for diffusive PDEs that preserves particle structure and converges to classical solutions under regularity assumptions.
Findings
Method accurately approximates solutions to diffusion equations.
Convergence proven for regularized energies and gradient flows.
Numerical examples demonstrate convergence rate and qualitative properties.
Abstract
As a counterpoint to classical stochastic particle methods for diffusion, we develop a deterministic particle method for linear and nonlinear diffusion. At first glance, deterministic particle methods are incompatible with diffusive partial differential equations since initial data given by sums of Dirac masses would be smoothed instantaneously: particles do not remain particles. Inspired by classical vortex blob methods, we introduce a nonlocal regularization of our velocity field that ensures particles do remain particles, and we apply this to develop a numerical blob method for a range of diffusive partial differential equations of Wasserstein gradient flow type, including the heat equation, the porous medium equation, the Fokker-Planck equation, the Keller-Segel equation, and its variants. Our choice of regularization is guided by the Wasserstein gradient flow structure, and the…
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