Chemo-Dynamical Clustering applied to APOGEE data: Re-Discovering Globular Clusters

TL;DR

This paper introduces a new chemo-dynamical clustering method that effectively identifies globular clusters and stellar streams in APOGEE data by combining chemical and kinematic information, surpassing classical chemical tagging techniques.

Contribution

The novel clustering algorithm integrates kinematic and chemical data to discover globular clusters and stellar streams without prior positional knowledge.

Findings

Successfully identified known globular clusters in APOGEE data.

Detected chemical anti-correlations consistent with previous optical studies.

Potential to discover new clusters and stellar streams in the Milky Way.

Abstract

We have developed a novel technique based on a clustering algorithm which searches for kinematically- and chemically-clustered stars in the APOGEE DR12 Cannon data. As compared to classical chemical tagging, the kinematic information included in our methodology allows us to identify stars that are members of known globular clusters with greater confidence. We apply our algorithm to the entire APOGEE catalog of 150,615 stars whose chemical abundances are derived by the Cannon. Our methodology found anti-correlations between the elements Al and Mg, Na and O, and C and N previously identified in the optical spectra in globular clusters, even though we omit these elements in our algorithm. Our algorithm identifies globular clusters without a priori knowledge of their locations in the sky. Thus, not only does this technique promise to discover new globular clusters, but it also allows us to identify candidate streams of kinematically- and chemically-clustered stars in the Milky Way.