4.7 Article

A Keplerian-based Hamiltonian splitting for gravitational N-body simulations

Journal

MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
Volume 440, Issue 1, Pages 719-730

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/mnras/stu282

Keywords

Methods: numerical

Funding

  1. CAPES Foundation (Brazil) [5772-11-7]
  2. Netherlands Research Council NWO [643.200.503, 639.073.803, 614.061.608]
  3. Netherlands Research School for Astronomy (NOVA)

Ask authors/readers for more resources

We developed a Keplerian-based Hamiltonian splitting for solving the gravitational N-body problem. This splitting allows us to approximate the solution of a general N-body problem by a composition of multiple, independently evolved two-body problems. While the Hamiltonian splitting is exact, we show that the composition of independent two-body problems results in a non-symplectic non-time-symmetric first-order map. A time-symmetric second-order map is then constructed by composing this basic first-order map with its self-adjoint. The resulting method is precise for each individual two-body solution and produces quick and accurate results for near-Keplerian N-body systems, like planetary systems or a cluster of stars that orbit a supermassive black hole. The method is also suitable for integration of N-body systems with intrinsic hierarchies, like a star cluster with primordial binaries. The superposition of Kepler solutions for each pair of particles makes the method excellently suited for parallel computing; we achieve greater than or similar to 64 per cent efficiency for only eight particles per core, but close to perfect scaling for 16 384 particles on a 128 core distributed-memory computer. We present several implementations in sakura, one of which is publicly available via the amuse framework.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available