  The local arrangement of atoms is one of the most important predictors of
mechanical and functional properties of materials. However, algorithms for
identifying the geometrical arrangements of atoms in complex materials systems
are lacking. To address this challenge, we present a point-pattern matching
algorithm that can detect instances of a `template' structure in a given set of
atom coordinates. To our knowledge this is the first geometrical comparison
technique for atomistic configurations with very different number of atoms, and
when the optimal rotations and translations required to align the
configurations are unknown. The pattern matching algorithm can be combined with
an appropriate set of metrics to quantify the similarity or dissimilarity
between configurations of atoms. We demonstrate the unique capabilities of the
point-pattern matching algorithm using two examples where the automated
analysis of local atomistic structure can help advance the understanding of
structure-property relationships in material science: (a) identifying local
three-dimensional polyhedral units along interfacial defects, and (b) the
analysis of quasi-icosahedral topologies in the atomistic structure of metallic
glasses. We anticipate that the pattern matching algorithm will be applicable
in the analysis of atomistic structures in broad areas of condensed matter
systems, including biological molecules, polymers and disordered metallic
systems. An online implementation of the algorithm is provided via the open
source code hosted on GitHub (https://github.com/spatala/ppm3d).
