The Milky Way bar/bulge in proper motions: a 3D view from VIRAC and Gaia

• Published in: Monthly notices of the Royal Astronomical Society 2019-11, Vol.489 (3), p.3519-3538
• Main Authors: Clarke, Jonathan P, Wegg, Christopher, Gerhard, Ortwin, Smith, Leigh C, Lucas, Phil W, Wylie, Shola M
• Format: Article
• Language: English
• Subjects: Astrophysics; Physics
• ISSN: 0035-8711; 1365-2966
• DOI: 10.1093/mnras/stz2382

Abstract We have derived absolute proper motions of the entire Galactic bulge region from VVV Infrared Astrometric Catalogue (VIRAC) and Gaia. We present these both as integrated on-sky maps and, after isolating standard candle red clump (RC) stars, as a function of distance using RC magnitude as a proxy. These data provide a new global, 3D view of the Milky Way barred bulge kinematics. We find a gradient in the mean longitudinal proper motion, $\langle \mu _ l^\star \rangle $, between the different sides of the bar, which is sensitive to the bar pattern speed. The split RC has distinct proper motions and is colder than other stars at similar distance. The proper motion correlation map has a quadrupole pattern in all magnitude slices showing no evidence for a separate, more axisymmetric inner bulge component. The line-of-sight integrated kinematic maps show a high central velocity dispersion surrounded by a more asymmetric dispersion profile. $\sigma _{\mu _l} / \sigma _{\mu _b}$ is smallest, ≈1.1, near the minor axis and reaches ≈1.4 near the disc plane. The integrated $\langle \mu_b\rangle$ pattern signals a superposition of bar rotation and internal streaming motion, with the near part shrinking in latitude and the far part expanding. To understand and interpret these remarkable data, we compare to a made-to-measure barred dynamical model, folding in the VIRAC selection function to construct mock maps. We find that our model of the barred bulge, with a pattern speed of 37.5 $\mathrm{ \mathrm{ km \, s^{-1}} \, kpc^{-1} }$, is able to reproduce all observed features impressively well. Dynamical models like this will be key to unlocking the full potential of these data.