Trials and Tribulations of Chemodynamical Tagging: Investigating the Recovery of Open Clusters in the Gaia Data Release 3 and GALAH Data Release 4 Catalogs

Abstract Chemodynamical tagging has been suggested as a powerful tool to trace stars back to their birth clusters. However, the efficacy of chemodynamical tagging as a means to recover individual stellar clusters is still under debate. In this study, we present a detailed investigation of chemodynamical tagging of open clusters using both dynamical and chemical data from the Gaia Data Release 3 and GALAH Data Release 4 surveys, respectively. Using a sample of open clusters and mock field stars, we conduct a bootstrap analysis to evaluate every unique combination of orbital components ( E , J R , J ϕ , J Z ) and chemical abundances ([X/Fe] for O, Na, Mg, Al, Si, K, Ca, Sc, Ti, Cr, Mn, Ni, Cu, Y, and Ba) on how well they recover open clusters when used as parameters in the clustering algorithm HDBSCAN. We find that using primarily dynamical orbital parameters leads to the highest recovery rate of open cluster stars. Nevertheless, even employing the best performing parameter combinations leads to low open cluster recovery rates. We find that, in most cases, chemodynamical tagging of open clusters using blind clustering algorithms is not efficient, which is in line with previous theoretical and observational work. However, we show that the addition of cuts based on metallicity, age, and birth radius in order to reduce the size of the clustering catalog can marginally improve the recovery rate of open clusters.