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arXiv · 2606.13793

A Scalable Fast Multipole Method Poisson Solver for the RAMSES code: I. Unigrid Algorithm

Jun-Young Lee·Romain Teyssier
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Abstract

We present a scalable Poisson solver with $O(N)$ complexity based on the fast multipole method (FMM) implemented in RAMSES. Our FMM constructs a hierarchy of FMM grids on top of the pre-existing Cartesian grid which is used to compute the force for hydrodynamics or particle-mesh simulations. In contrast to the $O(N)$ multigrid solver (MG) - an iterative method that requires multiple V-cycles through a multi-resolution hierarchy of Cartesian grids - the FMM algorithm performs just one upward pass through the same hierarchy, during which multipole expansions are accumulated and shifted, followed by a single downward pass, in which local expansions are propagated. Numerical tests indicate that FMM attains accuracy comparable to that of MG for smooth potentials and is particularly well-suited for problems with isolated boundary conditions, since it avoids the approximate Dirichlet boundary conditions required by MG schemes. Although in theory FMM requires around 30 times more floating-point operations than MG, its higher arithmetic intensity leads to comparable performance and better scalability relative to MG.

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Jun-Young Lee, Romain Teyssier. 2026-06-11. A Scalable Fast Multipole Method Poisson Solver for the RAMSES code: I. Unigrid Algorithm. https://arxiv.org/abs/2606.13793

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