Fourier Spectral Methods with Exponential Time Differencing for Space-Fractional Partial Differential Equations in Population Dynamics

TL;DR

This paper introduces a numerical method combining Fourier spectral techniques with exponential time differencing to solve multi-dimensional space-fractional PDEs in population dynamics, enabling efficient and accurate simulations.

Contribution

It develops a novel numerical approach for multi-component, multi-dimensional space-fractional PDEs using spectral and exponential time differencing methods.

Findings

Demonstrates the method's convergence and stability.

Analyzes the impact of fractional parameters on growth models.

Provides biological interpretation of model parameters.

Abstract

Physical laws governing population dynamics are generally expressed as differential equations. Research in recent decades has incorporated fractional-order (non-integer) derivatives into differential models of natural phenomena, such as reaction-diffusion systems. In this paper, we develop a method to numerically solve a multi-component and multi-dimensional space-fractional system. For space discretization, we apply a Fourier spectral method that is suited for multidimensional PDE systems. Efficient approximation of time-stepping is accomplished with a locally one dimensional exponential time differencing approach. We show the effect of different fractional parameters on growth models and consider the convergence, stability, and uniqueness of solutions, as well as the biological interpretation of parameters and boundary conditions.