Spectral solutions of PDEs on networks

To solve linear PDEs on metric graphs with standard coupling conditions (continuity and Kirchhoff's law), we develop and compare a spectral, a second-order finite difference, and a discontinuous Galerkin method. The spectral method yields eigenvalues and eigenvectors of arbitrary order with machine precision and converges exponentially. These eigenvectors provide a Fourier-like basis on which to expand the solution; however, more complex coupling conditions require additional research. The discontinuous Galerkin method provides approximations of arbitrary polynomial order; however computing high-order eigenvalues accurately requires the respective eigenvector to be well-resolved. The method allows arbitrary non-Kirchhoff flux conditions and requires special penalty terms at the vertices to enforce continuity of the solutions. For the finite difference method, the standard one-sided second-order finite difference stencil reduces the accuracy of the vertex solution to O (h(3/2)). To preserve overall second-order accuracy, we used ghost cells for each edge. For all three methods we provide the implementation details, their validation, and examples illustrating their performance for the eigenproblem, Poisson equation, and the wave equation. (C) 2021 IMACS. Published by Elsevier B.V. All rights reserved.

Automated summary

This study introduces and compares three methods for solving linear PDEs on metric graphs: spectral method, finite difference method, and discontinuous Galerkin method. The spectral method can obtain eigenvalues and eigenvectors of arbitrary order with machine precision; the discontinuous Galerkin method provides approximations of arbitrary polynomial order; while the finite difference method requires additional treatments to maintain accuracy.