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HOP: A New Group-Finding Algorithm for N-body Simulations

Daniel J. Eisenstein·Piet Hut
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Abstract

We describe a new method (HOP) for identifying groups of particles in N-body simulations. Having assigned to every particle an estimate of its local density, we associate each particle with the densest of the N_hop particles nearest to it. Repeating this process allows us to trace a path, within the particle set itself, from each particle in the direction of increasing density. The path ends when it reaches a particle that is its own densest neighbor; all particles reaching the same such particle are identified as a group. Combined with an adaptive smoothing kernel for finding the densities, this method is spatially adaptive, coordinate-free, and numerically straight-forward. One can proceed to process the output by truncating groups at a particular density contour and combining groups that share a (possibly different) density contour. While the resulting algorithm has several user-chosen parameters, we show that the results are insensitive to most of these, the exception being the outer density cutoff of the groups.

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Daniel J. Eisenstein, Piet Hut. 1997-12-16. HOP: A New Group-Finding Algorithm for N-body Simulations. https://doi.org/10.1086/305535

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