Computing solution landscape of nonlinear space-fractional problems via fast approximation algorithm
arXiv:2108.03141 · doi:10.1016/j.jcp.2022.111513
Abstract
The nonlinear space-fractional problems often allow multiple stationary solutions, which can be much more complicated than the corresponding integer-order problems. In this paper, we systematically compute the solution landscapes of nonlinear constant/variable-order space-fractional problems. A fast approximation algorithm is developed to deal with the variable-order spectral fractional Laplacian by approximating the variable-indexing Fourier modes, and then combined with saddle dynamics to construct the solution landscape of variable-order space-fractional phase field model. Numerical experiments are performed to substantiate the accuracy and efficiency of fast approximation algorithm and elucidate essential features of the stationary solutions of space-fractional phase field model. Furthermore, we demonstrate that the solution landscapes of spectral fractional Laplacian problems can be reconfigured by varying the diffusion coefficients in the corresponding integer-order problems.
References in corpus (7)
- Numerical methods for nonlocal and fractional models
- Searching the solution landscape by generalized high-index saddle dynamics
- Solution landscape of a reduced Landau-de Gennes model on a hexagon
- Solution landscape of the Onsager model identifies non-axisymmetric critical points
- Solution Landscapes of the Simplified Ericksen--Leslie Model and its Comparison with the Reduced Landau--de Gennes Model
- Modeling and Computation of Liquid Crystals
- The Spatially Variant Fractional Laplacian