Integration factor combined with level set method for reaction-diffusion systems with free boundary in high spatial dimensions

TL;DR

This paper develops an efficient numerical method combining exponential time differencing, embedded boundary, and level set techniques to solve reaction-diffusion systems with free boundaries in complex geometries, ensuring stability and accuracy.

Contribution

It introduces a novel coupling of ETD methods with embedded boundary and level set techniques for high-dimensional reaction-diffusion systems with free boundaries, improving computational efficiency and accuracy.

Findings

Method demonstrates high stability and accuracy in numerical tests.

Significant reduction in computational cost using Krylov subspace algorithms.

Effective handling of complex geometries and free boundary problems.

Abstract

For reaction-diffusion equations in irregular domain with moving boundaries, the numerical stability constraints from the reaction and diffusion terms often require very restricted time step size, while complex geometries may lead to difficulties in accuracy when discretizing the high-order derivatives on grid points near the boundary. It is very challenging to design numerical methods that can efficiently and accurately handle both difficulties. Applying an implicit scheme may be able to remove the stability constraints on the time step, however, it usually requires solving a large global system of nonlinear equations for each time step, and the computational cost could be significant. Integration factor (IF) or exponential differencing time (ETD) methods are one of the popular methods for temporal partial differential equations (PDEs) among many other methods. In our paper, we couple ETD methods with an embedded boundary method to solve a system of reaction-diffusion equations with complex geometries. In particular, we rewrite all ETD schemes into a linear combination of specific {\phi}-functions and apply one start-of-the-art algorithm to compute the matrix-vector multiplications, which offers significant computational advantages with adaptive Krylov subspaces. In addition, we extend this method by incorporating the level set method to solve the free boundary problem. The accuracy, stability, and efficiency of the developed method are demonstrated by numerical examples.