Peter R. Brune

Jaydeep P. Bardhan, Matthew G. Knepley, Peter R. Brune

In this paper, we present an analytical solution to nonlocal continuum electrostatics for an arbitrary charge distribution in a spherical solute. Our approach relies on two key steps: (1) re-formulating the PDE problem using boundary-integral equations, and (2) diagonalizing the boundary-integral operators using the fact their eigenfunctions are the surface spherical harmonics. To introduce this uncommon approach for analytical calculations in separable geometries, we rederive Kirkwood's classic results for a protein surrounded concentrically by a pure-water ion-exclusion layer and then a dilute electrolyte (modeled with the linearized Poisson--Boltzmann equation). Our main result, however, is an analytical method for calculating the reaction potential in a protein embedded in a nonlocal-dielectric solvent, the Lorentz model studied by Dogonadze and Kornyshev. The analytical method enables biophysicists to study the new nonlocal theory in a simple, computationally fast way; an open-source MATLAB implementation is included as supplemental information.

Peter R. Brune, Matthew G. Knepley, Barry F. Smith et al.

Most efficient linear solvers use composable algorithmic components, with the most common model being the combination of a Krylov accelerator and one or more preconditioners. A similar set of concepts may be used for nonlinear algebraic systems, where nonlinear composition of different nonlinear solvers may significantly improve the time to solution. We describe the basic concepts of nonlinear composition and preconditioning and present a number of solvers applicable to nonlinear partial differential equations. We have developed a software framework in order to easily explore the possible combinations of solvers. We show that the performance gains from using composed solvers can be substantial compared with gains from standard Newton-Krylov methods.

Peter R. Brune, Matthew G. Knepley, L. Ridgway Scott

The use of multigrid and related preconditioners with the finite element method is often limited by the difficulty of applying the algorithm effectively to a problem, especially when the domain has a complex shape or adaptive refinement. We introduce a simplification of a general topologically-motivated mesh coarsening algorithm for use in creating hierarchies of meshes for geometric unstructured multigrid methods. The connections between the guarantees of this technique and the quality criteria necessary for multigrid methods for non-quasi-uniform problems are noted. The implementation details, in particular those related to coarsening, remeshing, and interpolation, are discussed. Computational tests on pathological test cases from adaptive finite element methods show the performance of the technique.