2019
Journal article  Open Access

Fast solvers for two-dimensional fractional diffusion equations using rank structured matrices

Massei S., Mazza M., Robol L.

Computational Mathematics  Fractional operators  FOS: Mathematics  Sylvester equation  Hierarchical matrices  Fractional diffusion  Structured matrices  Mathematics - Numerical Analysis  15A24  65F10  35R11  Applied Mathematics  Numerical Analysis (math.NA) 

We consider the discretization of time-space diffusion equations with fractional derivatives in space and either one-dimensional (1D) or 2D spatial domains. The use of an implicit Euler scheme in time and finite differences or finite elements in space leads to a sequence of dense large scale linear systems describing the behavior of the solution over a time interval. We prove that the coefficient matrices arising in the 1D context are rank structured and can be efficiently represented using hierarchical formats (\scrH -matrices, HODLR). Quantitative estimates for the rank of the off-diagonal blocks of these matrices are presented. We analyze the use of HODLR arithmetic for solving the 1D case and we compare this strategy with existing methods that exploit the Toeplitz-like structure to precondition the GMRES iteration. The numerical tests demonstrate the convenience of the HODLR format when at least a reasonably low number of time steps is needed. Finally, we explain how these properties can be leveraged to design fast solvers for problems with 2D spatial domains that can be reformulated as matrix equations. The experiments show that the approach based on the use of rank-structured arithmetic is particularly effective and outperforms current state of the art techniques.

Source: SIAM journal on scientific computing (Print) 41 (2019): A2627–A2656. doi:10.1137/18M1180803

Publisher: Society for Industrial and Applied Mathematics,, Philadelphia, PA , Stati Uniti d'America


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BibTeX entry
@article{oai:it.cnr:prodotti:422761,
	title = {Fast solvers for two-dimensional fractional diffusion equations using rank structured matrices},
	author = {Massei S. and Mazza M. and Robol L.},
	publisher = {Society for Industrial and Applied Mathematics,, Philadelphia, PA , Stati Uniti d'America},
	doi = {10.1137/18m1180803 and 10.48550/arxiv.1804.05522},
	journal = {SIAM journal on scientific computing (Print)},
	volume = {41},
	year = {2019}
}