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A parameter-free, solid-angle based, nearest-neighbor algorithm
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10.1063/1.4729313
/content/aip/journal/jcp/136/23/10.1063/1.4729313
http://aip.metastore.ingenta.com/content/aip/journal/jcp/136/23/10.1063/1.4729313

Figures

Image of FIG. 1.
FIG. 1.

Definition of the angle θ i, j associated with a neighbor j of particle i. Here, r i, j is the distance between both particles and is the neighbor shell radius.

Image of FIG. 2.
FIG. 2.

2D comparison of the SANN and Voronoi algorithms. In all three panels we show a central particle with potential nearest neighbors A through F. In panel (a) we sketch the SANN algorithm: the green circle shows the shell radius, and particles B through F are identified as nearest neighbors. Note that in all panels the nearest neighbors are indicated with red lines. To facilitate the comparison between a Voronoi construction and the SANN algorithm, in panel (b) we make use of the fact that the SANN algorithm is scale free, i.e., = where 0.5r i, j is simply the distance from particle i to the midpoint between i and j, and is half the shell radius. In panel (b) the green circles have a radius equal to the half the shell radius of the center particle, and are centered around each particle; the black lines are constructed by finding the intersection of the green circles and indicate the width of the solid angle between the center particle and each of its neighbors, respectively. Finally, in panel (c) we show a Voronoi construction for the same set of particles. Note that the Voronoi construction finds an extra nearest neighbor, i.e., particle A.

Image of FIG. 3.
FIG. 3.

Nearest neighbors distribution P(N n ) for a Lennard-Jones liquid (panel a) and fcc crystal (panel b) obtained by fixed-distance cutoff (C), Voronoi construction (V) and SANN considering neighbors belonging to the first coordination shell (S). Panels (c) and (d) plot the pair correlation functions g(r), considering all particles, as a reference (thin grey dotted line), and g nn (r), considering only nearest neighbors (Voronoi (V) and SANN (S)) and next-nearest neighbors (SANN (S 2)), for both the liquid (c) and the fcc crystal (d). In addition, their fraction g nn (r)/g(r) is shown.

Image of FIG. 4.
FIG. 4.

Nearest-neighbor distribution and g(r) as in Figure 3, but for a monodisperse hard spheres system at ϕ = 0.54 (panels a and c) and ϕ = 0.61 (panels b and d).

Image of FIG. 5.
FIG. 5.

Nearest-neighbor distribution and g(r) as in Figure 3, but for both a 3-fold coordinated carbon liquid (panels a and c) and graphite crystal (panels b and d).

Image of FIG. 6.
FIG. 6.

Nearest-neighbor distribution and g(r) as in Figure 3, but for both a 4-fold coordinated carbon liquid (panels a and c) and diamond crystal (panels b and d).

Image of FIG. 7.
FIG. 7.

Simulation snapshot of 3-fold coordinated carbon graphite showing the first neighbors (yellow) of a center particle (gray). Surrounding particles that are not part of the neighborhood are shown in blue. (a) Voronoi construction; (b) SANN algorithm; and (c) Top-view on the center layer of panel b.

Image of FIG. 8.
FIG. 8.

Results for two-phase samples in a slab-geometry, with the two interfaces oriented normal to the x-direction. The two phases are (a) liquid-crystal and (b) liquid-vapor. Note that the densities of the liquid in both the cases are not same. For both samples the upper panel shows, as function of x-position, the average number of nearest neighbors, ⟨N Nb (x)⟩, and the lower panel the corresponding variance, , for each of the algorithms: fixed-distance cutoff (C) with r c = 1.5, Voronoi construction (V) and SANN considering neighbors belonging to the first coordination shell (S). Note the different scales on the y axis.

Image of FIG. 9.
FIG. 9.

Visual representation of the three algorithms in a two-phase liquid-vapor Lennard-Jones system: fixed-distance cutoff (top), Voronoi construction (center) and SANN (bottom). In each case, we select the same particles and check which neighbors are detected using each algorithm.

Image of FIG. 10.
FIG. 10.

Distribution of the local bond-order correlator d 6(i, j) using different neighbor criteria. Panel (a) shows results for Lennard-Jones fcc crystal (upper panel) and liquid phases (lower panel), panel (b) for the 3-fold coordinated carbon graphite (upper panel) and liquid (lower panel) phases, and panel (c) for the 4-fold coordinated carbon diamond (upper panel) and liquid (lower panel) phases. For the carbon phases the fixed-distance cutoff distance was set to 2.7 to include the next-nearest neighbors, as do inherently both the Voronoi and SANN algorithms.

Tables

Generic image for table
Table I.

Run-times in milliseconds of the fixed-distance cutoff (C), the Voronoi construction (V) and the SANN algorithm (S), and their ratios V/C and S/C. For details on the system samples we refer to Sec. III A, for implementation details to Sec. III B, and for the benchmarking procedure to the main text.

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/content/aip/journal/jcp/136/23/10.1063/1.4729313
2012-06-20
2014-04-20
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752b84549af89a08dbdd7fdb8b9568b5 journal.articlezxybnytfddd
Scitation: A parameter-free, solid-angle based, nearest-neighbor algorithm
http://aip.metastore.ingenta.com/content/aip/journal/jcp/136/23/10.1063/1.4729313
10.1063/1.4729313
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