Numerical Convergence in Smoothed Particle Hydrodynamics
Abstract
We study the convergence properties of smoothed particle hydrodynamics (SPH) using numerical tests and simple analytic considerations. Our analysis shows that formal numerical convergence is possible in SPH only in the joint limit , , and , where is the total number of particles, is the smoothing length, and is the number of neighbor particles within the smoothing volume used to compute smoothed estimates. Previous work has generally assumed that the conditions and are sufficient to achieve convergence, while holding fixed. We demonstrate that if is held fixed as the resolution is increased, there will be a residual source of error that does not vanish as and . Formal numerical convergence in SPH is possible only if is increased systematically as the resolution is improved. Using analytic arguments, we derive an optimal compromise scaling for by requiring that this source of error balance that present in the smoothing procedure. For typical choices of the smoothing kernel, we find . This means that if SPH is to be used as a numerically convergent method, the required computational cost does not scale with particle number as , but rather as , where , with a weak dependence on the form of the smoothing kernel.
Keywords
Cite
@article{arxiv.1410.4222,
title = {Numerical Convergence in Smoothed Particle Hydrodynamics},
author = {Qirong Zhu and Lars Hernquist and Yuexing Li},
journal= {arXiv preprint arXiv:1410.4222},
year = {2015}
}
Comments
The revised version accepted in ApJ, with typos corrected and references added