一种无参数、基于立体角的最近邻算法
A parameter-free, solid-angle based, nearest-neighbor algorithm
摘要：
我们提出了一个无参数的算法识别最近的邻居。该算法非常容易使用，并且与现有的识别最近邻的算法相比具有许多优点。这种基于立体角的最近邻算法（SANN）将立体角赋予每个可能的邻居，并通过立体角之和为4π的要求来确定截止半径。该算法可用于分析3D图像，无论是从实验还是理论，并且由于该算法具有较低的计算成本，因此也可以在模拟中“即时”使用。在本文中，我们描述了SANN算法，讨论其性能，并通过分析其在碳原子，Lennard-Jones粒子和硬球系统的体相以及在具有液晶和液-气界面的Lennard-Jones系统中的行为，将其与固定距离截断算法和Voronoi构造进行比较。
英文摘要：
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.
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