If we could map the Galactic halo structure, substructure, and kinematics with high precision and over a large volume, we could search for the faintest Milky Way satellites, measure the properties of the Galactic dark matter halo, and through comparisons with state-of-the-art simulations, constrain the theory of galaxy formation.
I will present one such map of the Galactic halo, traced using a sample of 45,000 RR Lyrae stars selected from the Pan-STARRS1 (PS1) survey, that covers three-quarters of the sky up to 120 kpc of the Sun. I will describe how I used machine learning to select the above sample from a large, but sparse multiband PS1 dataset, and how I plan to use similar datasets, such as those produced by LSST and ZTF, to study the far side of the Galaxy.
As the first preliminary result, I will present the deepest and widest view of the Sagittarius tidal stream, and demonstrate that the so-called Gemini stream (Drake et al. 2013), is simply a distant part of the Sagittarius stream.