Metrics for measuring distances in configuration spaces

Sadeghi, Ali and Ghasemi, S. Alireza and Schaefer, Bastian and Mohr, Stephan and Lill, Markus A. and Goedecker, Stefan. (2013) Metrics for measuring distances in configuration spaces. Journal of Chemical Physics, 139 (18). p. 184118.

Full text not available from this repository.

Official URL: https://edoc.unibas.ch/73853/

Downloads: Statistics Overview


In order to characterize molecular structures we introduce configurational fingerprint vectors which are counterparts of quantities used experimentally to identify structures. 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. In particular we show that these metrics are a perfect and computationally cheap replacement for the root-mean-square distance (RMSD) when one has to decide whether two noise contaminated configurations are identical or not. We introduce a Monte Carlo approach to obtain the global minimum of the RMSD between configurations, which is obtained from a global minimization over all translations, rotations, and permutations of atomic indices.
Faculties and Departments:05 Faculty of Science > Departement Physik > Physik > Physik (Goedecker)
UniBasel Contributors:Goedecker, Stefan
Item Type:Article, refereed
Article Subtype:Research Article
Publisher:AIP Publishing
Note:Publication type according to Uni Basel Research Database: Journal article
Identification Number:
Last Modified:22 Apr 2020 07:58
Deposited On:22 Apr 2020 07:58

Repository Staff Only: item control page