Abstract.
Many dark matter models predict small-scale substructure, including subhaloes, boson stars, axion miniclusters, and primordial black holes. In this talk, I will discuss how gravitational microlensing serves as a powerful probe of these scenarios. Microlensing occurs when a dark matter object temporarily magnifies the light of a distant star as it passes in front of it. I will describe the characteristic signals observed in surveys, highlighting how certain mass distributions produce distinctive light curve features due to optical effects like caustics. I will explore opportunities for detecting these microlensing signatures using machine learning techniques, including real-time anomaly detection on time-series data. Finally, I will discuss how microlenses embedded in galaxy cluster macrolenses offer unique insights, which even have implications for early universe cosmology.
(The slides will be available here)