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The first generation of large-scale chemical tagging surveys, in particularthe HERMES/GALAH million star survey, promises to vastly expand ourunderstanding of the chemical and dynamical evolution of the Galaxy. This,however, is contingent on our ability to confidently perform chemical taggingon such a large data-set. Chemical homogeneity has been observed across a rangeof elements within several Galactic open clusters, yet the level to which thisis the case globally, and particularly in comparison to the scatter acrossclusters themselves, is not well understood. The patterns of elements in coevalcluster members, occupying a complex chemical abundance space, are rooted inthe evolution, ultimately the nature of the very late stages, of earlygenerations of stars. The current astrophysical models of such stages are notyet sufficient to explain all observations, combining with our significant gapsin the understanding of star formation, makes this a difficult arena to tackletheoretically. Here, we describe a robust pair-wise metric used to gauge thechemical difference between two stellar components. This metric is then appliedto a database of high-resolution literature abundance sources to derive afunction describing the probability that two stars are of common evolutionaryorigin. With this cluster probability function, it will be possible to report aconfidence, grounded in empirical observational evidence, with which clustersare detected, independent of the group finding methods. This formulation isalso used to probe the role of chemical dimensionality, and that of individualchemical species, on the ability of chemical tagging to differentiate coevalgroups of stars.

Quantifying Chemical Tagging: Towards Robust Group Finding in the Galaxy