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Our findings show that the Barnes–Hut tree outperforms the binary tree in both cases.
A Barnes–Hut tree is used for treating self-gravity and updating the neighbour list of the particles.
However, we present a modified binary tree which is competitive with the Barnes–Hut tree for long-range physics and superior for short-range physics.
To overcome this obstacle we have developed an innovative parallelization strategy for Barnes–Hut tree codes on present and upcoming HPC multicore architectures.
Using a standard grain charging model along with a modified Barnes–Hut tree code for calculating grain dynamics, this paper examines the effect of including initial grain charging in coagulation of clouds of negative grains, positive grains, and a mixture of oppositely charged grains.
Box_tree is a Barnes_Hut tree code which has proven effective in modeling systems composed of large numbers of particles.
Similar(51)
This is accomplished in the current work using a Barnes-Hut tree code known as "Box_Tree".
I describe a modification of the Barnes-Hut tree algorithm together with a series of numerical tests of this method.
Vectorized algorithms for the force calculation and tree construction in the Barnes-Hut tree algorithm are described.
For long-range forces, we use a combination of the Barnes-Hut tree code and the leapfrog integrator.
Even with the Barnes-Hut tree algorithm, obtaining (boldsymbol {F}_{mathrm{soft},i}) is still costly and dominates the total calculation time (Oshino et al. 2011).
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