FOM Institute for Atomic and Molecular Physics, Science Park 104, 1098 XG Amsterdam, The Netherlands.
J Chem Phys. 2012 Jun 21;136(23):234107. doi: 10.1063/1.4729313.
We propose a parameter-free algorithm for the identification of nearest neighbors. The algorithm is very easy to use and has a number of advantages over existing algorithms to identify nearest-neighbors. This solid-angle based nearest-neighbor algorithm (SANN) attributes to each possible neighbor a solid angle and determines the cutoff radius by the requirement that the sum of the solid angles is 4π. The algorithm can be used to analyze 3D images, both from experiments as well as theory, and as the algorithm has a low computational cost, it can also be used "on the fly" in simulations. In this paper, we describe the SANN algorithm, discuss its properties, and compare it to both a fixed-distance cutoff algorithm and to a Voronoi construction by analyzing its behavior in bulk phases of systems of carbon atoms, Lennard-Jones particles and hard spheres as well as in Lennard-Jones systems with liquid-crystal and liquid-vapor interfaces.
我们提出了一种用于识别最近邻的无参算法。该算法使用非常简单，并且在识别最近邻方面优于现有的算法。这种基于立体角的最近邻算法（SANN）为每个可能的邻居赋予一个立体角，并通过要求立体角的总和为 4π 来确定截止半径。该算法可用于分析 3D 图像，包括实验和理论图像，并且由于该算法的计算成本较低，因此也可在模拟中“实时”使用。在本文中，我们描述了 SANN 算法，讨论了它的性质，并通过分析它在碳原子系统、Lennard-Jones 粒子和硬球的体相以及具有液晶和液-气相界面的 Lennard-Jones 系统中的行为，将其与固定距离截止算法和 Voronoi 构造进行了比较。
