Speaker
Description
Detecting faint stellar substructure in the Milky Way halo and its surroundings favours methods that remain sensitive to weak signals without restrictive assumptions about either the signal morphology or the Galactic background. We present recent applications of EagleEye, a model-independent anomaly detection framework that compares multidimensional data distributions to identify localized over- and underdensities relative to an empirical reference sample. We highlight two applications: the detection of faint dwarf galaxies around the Milky Way and the search for stellar wakes induced by its most massive satellites. As stellar wakes are expected to be exceptionally faint and difficult to model, yet offer a novel probe of dark matter substructure, they are a particularly exciting target for data-driven anomaly detection methods.