Point Group Analysis in Particle Simulation Data

TL;DR

This paper introduces an algorithm that analyzes point group symmetry directly from particle coordinates in simulation data, aiding in crystal structure identification and analysis of crystallographic order.

Contribution

The novel algorithm enables direct analysis of point group symmetry from particle data, improving structure classification and order detection in simulations.

Findings

Effective classification of local structures in particle data

Ability to analyze crystal orientation and order development

Potential for generalized order parameter applications

Abstract

A routine crystallography technique, crystal structure analysis, is rarely performed in computational condensed matter research. The lack of methods to identify and characterize crystal structures reliably in particle simulation data complicates the comparison of simulation outcomes to experiment and the discovery of new materials. Algorithms are sought that not only classify local structure but also analyze the type and degree of crystallographic order. Here, we develop an algorithm that analyzes point group symmetry directly from particle coordinates. The algorithm operates on functions defined on the surface of the sphere, such as the bond orientational order diagram. Other use cases are the orientation of crystals and adoption as generalized order parameters for detecting the appearance of order as well as following its development.