Discovering the Goddess of the Night with Machine Learning

          @misc{ scivideos_PIRSA:19090021,
            doi = {10.48660/19090021},
            url = {https://pirsa.org/19090021},
            author = {Lisanti, Miriangela},
            keywords = {Cosmology, Particle Physics, Strong Gravity},
            language = {en},
            title = {Discovering the Goddess of the Night with Machine Learning},
            publisher = {Perimeter Institute for Theoretical Physics},
            year = {2019},
            month = {sep},
            note = {PIRSA:19090021 see, \url{https://scivideos.org/index.php/pirsa/19090021}}
          }
          

Abstract

The Gaia mission is in the process of mapping nearly 1% of the Milky Way’s stars. This data set is unprecedented and provides a unique view into the formation history of our Galaxy and its associated dark matter halo. My talk will focus primarily on recent work using deep learning methods to classify Gaia stars that were born inside the Milky Way, versus those that were accreted from satellite mergers. Using these techniques, we discovered a vast stellar stream, called Nyx (after the Goddess of the Night), in the Solar vicinity that co-rotates with the Galactic disk. If Nyx is the remnant of a disrupted dwarf galaxy, it may provide the first evidence for an accreted stellar disk and a dark matter disk.