In this talk, I will explore the interfacing of simulations, observations, and machine learning techniques to construct a detailed map of Dark Matter in the Milky Way, focusing on the Galactic Center/Halo and dwarf galaxies. For the Galactic Halo, I will present a recent work that reveals a decline in the stellar circular velocity, inducing tensions with established estimates of the Milky Way's mass and Dark Matter content. I will discuss how the underestimated systematic errors in such a common methodology necessitates a revised approach that combines theory, observations, and machine learning. In dwarf galaxies, I will present a novel Graph Neural Network methodology that facilitates the accurate extraction of Dark Matter density profiles, validated against realistic simulations. I will conclude with a discussion on the future trajectory of astroparticle physics, emphasizing the need for the integration of astrophysical probes with experimental Dark Matter research, potentially leading to a better understanding of the nature of Dark Matter.

Speaker: Lina Necib (Massachusetts Institute of Technology)

The 2025 Spring Colloquium talks are held on Wednesdays at 3:00 PM. This colloquium is hosted by STScI and will be held as an in-person and virtual event.

You may join in person at STScI’s John N. Bahcall Auditorium or virtually on STScI's Live Science Events Facebook page.

Please direct questions or comments to contact above. The 2025 Spring Colloquium Committee members are: Nestor Espinoza (STScI), Joel Green (STScI), Nick Indriolo (STScI), Elena Manjavacas (STScI), Namrata Roy (JHU), Kevin Schlaufman (JHU), Ethan Vishniac (JHU).