## A Method to Compute Periodic Sums

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2013-10-09##### Автор

Gumerov, Nail A.

Duraiswami, Ramani

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In a number of problems in computational physics, a finite sum of kernel functions centered at N particle locations located in a box in three dimensions must be extended by imposing periodic boundary conditions on box boundaries. Even though the finite sum can be efficiently computed via fast summation algorithms, such as the fast multipole method (FMM), the periodized extension, posed as an infinite sum of kernel functions, centered at the particle locations in the box, and their images, is usually treated via a different algorithm, Ewald summation. This is then accelerated via the fast Fourier transform (FFT). A method for computing this periodized sum just using a blackbox finite fast summation algorithm is presented in this paper. The method splits the periodized sum in to two parts. The first, comprising the contribution of all points outside a large sphere enclosing the box, and some of its neighbors, is approximated inside the box by a collection of kernel functions (“sources”) placed on the surface of the sphere. These are approximated within the box using an expansion in terms of spectrally convergent local basis functions. The second part, comprising the part inside the sphere, and including the box and its immediate neighborhood, is treated via the summation algorithm. The coefficients of the sources are determined by least squares collocation of the periodicity condition of the total potential, imposed on a circumspherical surface for the box. While the method is presented in general, details are worked out for the case of evaluating potentials and forces due to electrostatically charged particles in a box. Results show that when used with the FMM, the periodized sum can be computed to any specified accuracy, at a cost of about twice the cost of the free-space FMM with the same accuracy. Several technical details and efficient algorithms for auxiliary computations are also provided, as are numerical comparisons.

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