An Adaptive Fast Gauss Transform in Two Dimensions

Jun Wang Yau Mathematical Sciences Center, Tsinghua University Leslie Greengard Courant Institute, New York University

Numerical Analysis and Scientific Computing mathscidoc:2205.25001

Journal of Computational Physics, 40, (3), 2018.5
A variety of problems in computational physics and engineering require the convolu- tion of the heat kernel (a Gaussian) with either discrete sources, densities supported on boundaries, or continuous volume distributions. We present a unified fast Gauss transform for this purpose in two dimensions, making use of an adaptive quad-tree discretization on a unit square which is assumed to contain all sources. Our implementation permits either free-space or periodic boundary conditions to be imposed, and is efficient for any choice of variance in the Gaussian.
fast Gauss transform, heat equation, adaptive mesh refinement
[ Download ] [ 2022-05-17 12:13:28 uploaded by jwang_thu ] [ 304 downloads ] [ 0 comments ]
  title={An Adaptive Fast Gauss Transform in Two Dimensions},
  author={Jun Wang, and Leslie Greengard},
  booktitle={Journal of Computational Physics},
Jun Wang, and Leslie Greengard. An Adaptive Fast Gauss Transform in Two Dimensions. 2018. Vol. 40. In Journal of Computational Physics.
Please log in for comment!
Contact us: | Copyright Reserved