Tidal debris from Omega Centauri discovered with unsupervised machine learning
Kris Youakim, Karin Lind, and Iryna Kushniruk

TL;DR
This study uses unsupervised machine learning to identify tidal debris from Omega Centauri in high-dimensional stellar data, revealing its extensive halo distribution and constraining its accretion history.
Contribution
The paper introduces an unsupervised learning approach to detect tidally stripped stars of Omega Centauri using combined chemical and dynamical data, providing new insights into its origin.
Findings
Candidates for Omega Centauri debris extend over 50 degrees in the halo.
The accretion of Omega Centauri likely occurred over 4-7 billion years ago.
Results support Omega Centauri being the core of a disrupted dwarf galaxy.
Abstract
The gravitational interactions between the Milky Way and in-falling satellites offer a wealth of information about the formation and evolution of our Galaxy. In this paper, we explore the high-dimensionality of the GALAH DR3 plus Gaia eDR3 data set to identify new tidally stripped candidate stars of the nearby star cluster Omega Centauri (). We investigate both the chemical and dynamical parameter space simultaneously, and identify cluster candidates that are spatially separated from the main cluster body, in regions where contamination by halo field stars is high. Most notably, we find candidates for scattered in the halo extending to more than away from the main body of the cluster. Using a grid of simulated stellar streams generated with like orbital properties, we then compare the on sky distribution of…
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Taxonomy
TopicsStellar, planetary, and galactic studies · Astronomy and Astrophysical Research · Gamma-ray bursts and supernovae
