Fast alternating-direction finite difference methods for three-dimensional space-fractional diffusion equations

  • Authors:
  • Hong Wang;Ning Du

  • Affiliations:
  • School of Mathematics, Shandong University, Jinan, Shandong 250100, China and Department of Mathematics, University of South Carolina, Columbia, SC 29208, USA;School of Mathematics, Shandong University, Jinan, Shandong 250100, China

  • Venue:
  • Journal of Computational Physics
  • Year:
  • 2014

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Abstract

Fractional diffusion equations model phenomena exhibiting anomalous diffusion that cannot be modeled accurately by second-order diffusion equations. Because of the nonlocal property of fractional differential operators, numerical methods for space-fractional diffusion equations generate dense or even full coefficient matrices with complicated structures. Traditionally, these methods were solved via Gaussian elimination, which requires computational work of O(N^3) per time step and O(N^2) of memory to store where N is the number of spatial grid points in the discretization. The significant computational work and memory requirement of these methods makes a numerical simulation of three-dimensional space-fractional diffusion equations computationally prohibitively expensive. We present an alternating-direction implicit (ADI) finite difference formulation for space-fractional diffusion equations in three space dimensions and prove its unconditional stability and convergence rate provided that the fractional partial difference operators along x-,@?y-,@?z-directions commute. We base on the ADI formulation to develop a fast iterative ADI finite difference method, which has a computational work count of O(NlogN) per iteration at each time step and a memory requirement of O(N). We also develop a fast multistep ADI finite difference method, which has a computational work count of O(Nlog^2N) per time step and a memory requirement of O(NlogN). Numerical experiments of a three-dimensional space-fractional diffusion equation show that these both fast methods retain the same accuracy as the regular three-dimensional implicit finite difference method, but have significantly improved computational cost and memory requirement. These numerical experiments show the utility of the fast method.