title: Permutation-invariant distance between atomic configurations.
abstract: We present a permutation-invariant distance between atomic configurations, defined through a functional representation of atomic positions. This distance enables us to directly compare different atomic environments with an arbitrary number of particles, without going through a space of reduced dimensionality (i.e., fingerprints) as an intermediate step. Moreover, this distance is naturally invariant through permutations of atoms, avoiding the time consuming associated minimization required by other common criteria (like the root mean square distance). Finally, the invariance through global rotations is accounted for by a minimization procedure in the space of rotations solved by Monte Carlo simulated annealing. A formal framework is also introduced, showing that the distance we propose verifies the property of a metric on the space of atomic configurations. Two examples of applications are proposed. The first one consists in evaluating faithfulness of some fingerprints (or descriptors), i.e., their capacity to represent the structural information of a configuration. The second application concerns structural analysis, where our distance proves to be efficient in discriminating different local structures and even classifying their degree of similarity.
authors.affiliation: CEA, DAM, DIF, F-91297 Arpajon, France.
authors.forename: Grégoire
authors.initials: G
authors.lastname: Ferré
authors.affiliation: CEA, DAM, DIF, F-91297 Arpajon, France.
authors.forename: Jean-Bernard
authors.initials: JB
authors.lastname: Maillet
authors.affiliation: Université Paris-Est, CERMICS (ENPC), INRIA, F-77455 Marne-la-Vallée, France.
authors.forename: Gabriel
authors.initials: G
authors.lastname: Stoltz
mesh_terms: D003198:Computer Simulation; D000069550:Machine Learning; D008956:Models, Chemical; D009010:Monte Carlo Method; D012399:Rotation