An Adaptive Fast Algorithm for Periodic Coulomb Lattice Sums in Arbitrary Unit Cells

Abstract

We present a fast algorithm for evaluating conditionally convergent Coulomb lattice sums, governed by the Laplace equation with periodic boundary conditions on arbitrary unit cells (oblique in 2D, triclinic in 3D) and arbitrary particle distributions. The algorithm extends the dual-space multilevel kernel-splitting (DMK) framework to this context. The root of the adaptive tree is now a rectangular grid of cubes consisting of an inner block covering the unit cell and a surrounding halo of image cubes, rather than a single cube, and the smooth top-level periodic kernel -- the only term that requires the consideration of conditional convergence issues -- is evaluated by the ``five-step procedure" used in fast Ewald summation: spreading, fast Fourier transform (FFT), diagonal scaling, inverse FFT, and interpolation. The resulting complexity is $O(N)$ for fixed cell shape. Benchmarked against the periodic fast multipole method on highly nonuniform source distributions, our 2D algorithm is roughly an order of magnitude faster across particle counts and target precisions; in three dimensions, it is often as fast as the free-space DMK on the same sources, even for triclinic cells with edge-length ratios up to roughly $17$.