Ali Sadeghi, S. Alireza Ghasemi, Markus A. Lill, Stefan Goedecker
In order to characterize molecular structures we introduce configurational fingerprint vectors which are related to quantities used experimentally to identify structures. Components of such vectors can be associated to individual atoms and can then serve as an atomic fingerprint that identifies an atom within a structure. The Euclidean distance between the configurational fingerprint vectors satisfies the properties of a metric and can therefore safely be used to measure dissimilarities between configurations in the high dimensional configuration space. We show that these metrics correlate very well with the RMSD between two configurations if this RMSD is obtained from a global minimization over all translations, rotations and permutations of atomic indices. We introduce a Monte Carlo approach to obtain this global minimum of the RMSD between configurations where atomic fingerprints are used to enhance the performance of the procedure.
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http://arxiv.org/abs/1302.2322
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