2026A&A...706A.298C

Context. Although many globular clusters (GCs) have been identified in the Galaxy, their population is estimated to be incomplete, especially in regions with significant crowding and/or interstellar extinction, such as the Galactic bulge and plane. RR Lyrae stars, as bright standard candles and tracers of old populations, hold immense potential in the search for GCs in these regions. Furthermore, large catalogs of RR Lyrae stars in these areas have become available in recent years.
Aims. We aim to build a sample of RR Lyrae stars with six-dimensional information (three-dimensional positions, proper motions, and metallicities) in the Galactic plane and bulge, and to exploit it with a hierarchical clustering algorithm to search for new Galactic substructures.
Methods. We build a sample of fundamental-mode RR Lyrae (RRab) stars in the Galactic plane and bulge with positions, distances, proper motions, and photometric metallicity estimates, using data from the Gaia and VVV surveys. Using a clustering algorithm calibrated to optimize the recovery of GCs, we form groups of RRab stars with similar positions in the six-dimensional space studied. Finally, to identify the most promising RRab groups among the many artifacts produced by the clustering algorithm, we compare their properties with those of known GCs.
Results. We find many RRab groups associated with known Galactic GCs. Additionally, we estimate the first RR Lyrae-based distances for the GCs BH 140 and NGC 5986, further constraining their positions in the Milky Way. We detect small groups of two to three RRab stars, located at distances of up to ∼ 25 kpc, that are not associated with any known GC, but exhibit GC-like distributions across all six parameters analyzed. Several of these groups - mostly pairs - are found toward the Galactic bulge, but have distinct proper motions or distances, indicating that they may not belong to the bulge population.
Conclusions. By exploiting an RRab sample in the Galactic plane and bulge with a hierarchical clustering algorithm, we identify dozens of groups displaying GC-like properties, which are excellent candidates for further follow-up observations. Furthermore, future radial velocity measurements could evaluate if the RRab members of our groups are truly moving together.