Spectral fractional Laplacian¶
SpectralFractionalLaplacian(u, s, bcs=...) is the fractional power of a
discrete Laplacian. Complete homogeneous exterior bcs select the Dirichlet
realization. Omitting bcs selects the natural homogeneous Neumann
realization. With eigenpairs \(\{(\lambda_k,q_k)\}\) of the selected positive
Laplacian, orthonormal in
\(L^2(\Omega)\),
The finite-element eigenproblem is \(Kq_k=\lambda_kMq_k\) with the selected boundary realization and \(q_i^TMq_j=\delta_{ij}\), so the discrete operator is
Discretization¶
Yonderdrake never forms the eigendecomposition. It evaluates the Balakrishnan integral representation of \(A_h^s\) with sinc quadrature, which turns each application into a sum of shifted elliptic solves that stay distributed.
sinc_truncation_targetcontrols the quadrature model only. It is a truncation estimate for the sinc rule. Mesh resolution controls the finite-element error. Targets below meaningfulfloat64precision are clamped with a warning. Requests requiring more than 100,000 nodes are rejected.shift_cachetrades setup cost against memory:"stream"keeps two shifted solvers,"all"caches one matrix and KSP per shift.diagnostics()reports node count, model estimate, setups, assemblies, solves, and reuse.
Requirements: \(0<s<1\). Dirichlet conditions must be homogeneous and cover the complete exterior boundary. With natural Neumann conditions, constants form the zero eigenspace and their fractional-Laplacian action is zero.
Refine the sinc target on a fixed mesh before measuring finite-element convergence. On a coarse mesh the discretization error dominates and tighter sinc targets change nothing.
Sources¶
Bonito and Pasciak (2015) for fractional powers of elliptic operators, and Bonito, Lei, and Pasciak (2019) for the sinc quadrature analysis.
The Riesz operator uses a zero-exterior realization. The periodic Fourier operator uses a periodic realization. See the comparison of spatial realizations.