Fast Multipole Methods for $N$-body Simulations of Collisional Star Systems
Diptajyoti Mukherjee, Qirong Zhu, Hy Trac, and Carl L. Rodriguez

TL;DR
This paper introduces an optimized Fast Multipole Method (FMM) implementation, Taichi, enabling accurate, large-scale collisional star cluster simulations that are computationally more efficient than traditional direct $N$-body methods.
Contribution
The paper adapts a tree-based FMM with error control and acceleration techniques for collisional $N$-body simulations, achieving accuracy comparable to direct summation for large $N$ and improving computational efficiency.
Findings
Taichi achieves direct-summation accuracy for $N>10^4$.
The code accurately models collisional effects like dynamical friction.
Taichi outperforms other CPU-based codes in efficiency for large systems.
Abstract
Direct -body simulations of star clusters are accurate but expensive, largely due to the numerous pairwise force calculations. To solve the post-million-body problem, it will be necessary to use approximate force solvers, such as tree codes. In this work, we adapt a tree-based, optimized Fast Multipole Method (FMM) to the collisional -body problem. The use of a rotation-accelerated translation operator and an error-controlled cell opening criterion leads to a code that can be tuned to arbitrary accuracy. We demonstrate that our code, Taichi, can be as accurate as direct summation when . This opens up the possibility of performing large-, star-by-star simulations of massive stellar clusters, and would permit large parameter space studies that would require years with the current generation of direct summation codes. Using a series of tests and…
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