Constraining the Milky Way Mass Profile with Phase-Space Distribution of Satellite Galaxies

Abstract

We estimate the Milky Way (MW) halo properties using satellite kinematic data including the latest measurements from Gaia DR2. With a simulation-based 6D phase-space distribution function (DF) of satellite kinematics, we can infer halo properties efficiently and without bias, and handle the selection function and measurement errors rigorously in the Bayesian framework. Applying our DF from the EAGLE simulation to 28 satellites, we obtain an MW halo mass of $M=1.23_{-0.18}^{+0.21}\times 10^{12}{M}_{\odot }$ and a concentration of $c=9.4_{-2.1}^{+2.8}$ with the prior based on the $M$-$c$ relation. The inferred mass profile is consistent with previous measurements but with better precision and reliability due to the improved methodology and data. Potential improvement is illustrated by combining satellite data and stellar rotation curves. Using our EAGLE DF and best-fit MW potential, we provide much more precise estimates of kinematics for those satellites with uncertain measurements. Compared to the EAGLE DF, which matches the observed satellite kinematics very well, the DF from the semi-analytical model based on the dark-matter-only simulation Millennium II (SAM-MII) over-represents satellites with small radii and velocities. We attribute this difference to less disruption of satellites with small pericenter distances in the SAM-MII simulation. By varying the disruption rate of such satellites in this simulation, we estimate a $\sim 5\%$ scatter in the inferred MW halo mass among hydrodynamics-based simulations.

arXiv commentAccepted for publication in ApJ; data tables available at https://github.com/syrte/mw_sats_kin

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