16,756 research outputs found
Fast, adaptive, high order accurate discretization of the Lippmann-Schwinger equation in two dimension
We present a fast direct solver for two dimensional scattering problems,
where an incident wave impinges on a penetrable medium with compact support. We
represent the scattered field using a volume potential whose kernel is the
outgoing Green's function for the exterior domain. Inserting this
representation into the governing partial differential equation, we obtain an
integral equation of the Lippmann-Schwinger type. The principal contribution
here is the development of an automatically adaptive, high-order accurate
discretization based on a quad tree data structure which provides rapid access
to arbitrary elements of the discretized system matrix. This permits the
straightforward application of state-of-the-art algorithms for constructing
compressed versions of the solution operator. These solvers typically require
work, where denotes the number of degrees of freedom. We
demonstrate the performance of the method for a variety of problems in both the
low and high frequency regimes.Comment: 18 page
Shenfun -- automating the spectral Galerkin method
With the shenfun Python module (github.com/spectralDNS/shenfun) an effort is
made towards automating the implementation of the spectral Galerkin method for
simple tensor product domains, consisting of (currently) one non-periodic and
any number of periodic directions. The user interface to shenfun is
intentionally made very similar to FEniCS (fenicsproject.org). Partial
Differential Equations are represented through weak variational forms and
solved using efficient direct solvers where available. MPI decomposition is
achieved through the {mpi4py-fft} module (bitbucket.org/mpi4py/mpi4py-fft), and
all developed solver may, with no additional effort, be run on supercomputers
using thousands of processors. Complete solvers are shown for the linear
Poisson and biharmonic problems, as well as the nonlinear and time-dependent
Ginzburg-Landau equation.Comment: Presented at MekIT'17, the 9th National Conference on Computational
Mechanic
- …