Abstract

ABSTRACT Three-body interactions can eject stars from the core of a globular cluster, causing them to enter the Galactic halo as extra-tidal stars. While finding extra-tidal stars is imperative for understanding cluster evolution, connecting isolated extra-tidal field stars back to their birth cluster is extremely difficult. In this work, we present a new methodology consisting of high-dimensional data analysis and a particle spray code to identify extra-tidal stars of any Galactic globular cluster using M3 as a case study. Using the t-Stochastic Neighbour Embedding and Uniform Manifold Approximation and Projection machine learning dimensionality reduction algorithms, we first identify a set of 103 extra-tidal candidates in the APOGEE DR17 data catalogue with chemical abundances similar to M3 stars. To confirm each candidate’s extra-tidal nature, we introduce corespray – a new python-based three-body particle spray code that simulates extra-tidal stars for any Galactic globular cluster. Using Gaia EDR3 proper motions and APOGEE DR17 radial velocities, we apply multivariate Gaussian modelling and an extreme deconvolution to identify the extra-tidal candidates that are more likely to be associated with a distribution of corespray-simulated M3 extra-tidal stars than the field. Through these methods, we identify 10 new high-probability extra-tidal stars produced via three-body interactions in M3. We also explore whether any of our extra-tidal candidates are consistent with being ejected from M3 through different dynamical processes. Future applications of corespray will yield better understandings of core dynamics, star formation histories, and binary fractions in globular clusters.

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