Substructure in the stellar halo near the Sun. I. Data-driven clustering in Integrals of Motion space
S. Sofie L\"ovdal, Tom\'as Ruiz-Lara, Helmer H. Koppelman, Tadafumi, Matsuno, Emma Dodd, Amina Helmi

TL;DR
This study develops a robust, data-driven clustering method using integrals of motion to identify and analyze substructures in the stellar halo near the Sun, revealing complex relationships and multiple significant streams.
Contribution
The paper introduces a novel hierarchical clustering approach combined with statistical significance testing for identifying halo substructures in integrals of motion space.
Findings
Identified 67 highly significant clusters containing 12% of halo stars.
Discovered 232 subgroups or streams in velocity space.
Revealed complex relationships suggesting at least 6 main halo structures.
Abstract
Aims: Develop a data-driven and statistically based method for finding such clumps in Integrals of Motion space for nearby halo stars and evaluating their significance robustly. Methods: We use data from Gaia EDR3 extended with radial velocities from ground-based spectroscopic surveys to construct a sample of halo stars within 2.5 kpc from the Sun. We apply a hierarchical clustering method that uses the single linkage algorithm in a 3D space defined by the commonly used integrals of motion energy , together with two components of the angular momentum, and . To evaluate the statistical significance of the clusters found, we compare the density within an ellipsoidal region centered on the cluster to that of random sets with similar global dynamical properties. We pick out the signal at the location of their maximum statistical significance in the hierarchical tree. We…
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Taxonomy
TopicsStellar, planetary, and galactic studies · Astronomy and Astrophysical Research · Educational Leadership and Practices
