‘Skinny Milky Way please’, says Sagittarius

• Published in: Monthly notices of the Royal Astronomical Society Vol. 445; no. 4; pp. 3788 - 3802
• Main Authors: Gibbons, S. L. J., Belokurov, V., Evans, N. W.
• Format: Journal Article
• Language: English
• Published: London Oxford University Press 21.12.2014
• Subjects: Algorithms; Astronomy; Galactic mass; Gravity; Inference; Kinematics; Milky Way; Milky Way Galaxy; Orbitals; Planets; Precession; Satellites; Streams; Galaxy: halo; galaxies: dwarf; Galaxy: kinematics and dynamics; Galaxy: fundamental parameters
• ISSN: 0035-8711; 1365-2966
• DOI: 10.1093/mnras/stu1986

Motivated by recent observations of the Sagittarius stream, we devise a rapid algorithm to generate faithful representations of the centroids of stellar tidal streams formed in a disruption of a progenitor of an arbitrary mass in an arbitrary potential. Our method works by releasing swarms of test particles at the Lagrange points around the satellite and subsequently evolving them in a combined potential of the host and the progenitor. We stress that the action of the progenitor's gravity is crucial to making streams that look almost indistinguishable from the N-body realizations, as indeed ours do. The method is tested on mock stream data in three different Milky Way potentials with increasing complexity, and is shown to deliver unbiased inference on the Galactic mass distribution out to large radii. When applied to the observations of the Sagittarius stream, our model gives a natural explanation of the stream's apocentric distances and the differential orbital precession. We, therefore, provide a new independent measurement of the Galactic mass distribution beyond 50 kpc. The Sagittarius stream model favours a light Milky Way with the mass 4.1 ± 0.4 × 1011 M⊙ at 100 kpc, which can be extrapolated to 5.6 ± 1.2 × 1011 M⊙ at 200 kpc. Such a low mass for the Milky Way Galaxy is in good agreement with estimates from the kinematics of halo stars and from the satellite galaxies (once Leo I is removed from the sample). It entirely removes the ‘Too Big To Fail Problem’.