A fast spectral sum-of-Gaussians method for electrostatic summation in quasi-2D systems
The quasi-2D electrostatic systems, characterized by periodicity in two dimensions with a free third dimension, have garnered significant interest in many fields. We apply the sum-of-Gaussians (SOG) approximation to the Laplace kernel, dividing the interactions into near-field, mid-range, and long-r...
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Zusammenfassung: | The quasi-2D electrostatic systems, characterized by periodicity in two
dimensions with a free third dimension, have garnered significant interest in
many fields. We apply the sum-of-Gaussians (SOG) approximation to the Laplace
kernel, dividing the interactions into near-field, mid-range, and long-range
components. The near-field component, singular but compactly supported in a
local domain, is directly calculated. The mid-range component is managed using
a procedure similar to nonuniform fast Fourier transforms in three dimensions.
The long-range component, which includes Gaussians of large variance, is
treated with polynomial interpolation/anterpolation in the free dimension and
Fourier spectral solver in the other two dimensions on proxy points. Unlike the
fast Ewald summation, which requires extensive zero padding in the case of high
aspect ratios, the separability of Gaussians allows us to handle such case
without any zero padding in the free direction. Furthermore, while NUFFTs
typically rely on certain upsampling in each dimension, and the truncated
kernel method introduces an additional factor of upsampling due to kernel
oscillation, our scheme eliminates the need for upsampling in any direction due
to the smoothness of Gaussians, significantly reducing computational cost for
large-scale problems. Finally, whereas all periodic fast multipole methods
require dividing the periodic tiling into a smooth far part and a near part
containing its nearest neighboring cells, our scheme operates directly on the
fundamental cell, resulting in better performance with simpler implementation.
We provide a rigorous error analysis showing that upsampling is not required in
NUFFT-like steps, achieving $O(N\log N)$ complexity with a small prefactor. The
performance of the scheme is demonstrated via extensive numerical experiments. |
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DOI: | 10.48550/arxiv.2412.04595 |