PIRSA:19090021

Discovering the Goddess of the Night with Machine Learning

Lisanti, M. (2019). Discovering the Goddess of the Night with Machine Learning. Perimeter Institute. https://pirsa.org/19090021

Lisanti, Miriangela. Discovering the Goddess of the Night with Machine Learning. Perimeter Institute, Sep. 06, 2019, https://pirsa.org/19090021 

          @misc{ pirsa_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},
            year = {2019},
            month = {sep},
            note = {PIRSA:19090021 see, \url{https://pirsa.org}}
          }

Miriangela Lisanti Princeton University

DOI 10.48660/19090021
Collection
Talk Type Conference
Subject

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.