134.04D Bayesian Mass Estimates of the Milky Way: Inferring the Mass Profile from Globular Cluster Kinematics (Gwendolyn Eadie)

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Jan 4th at 2:40 PM until 3:00 PM

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Author(s): Gwendolyn Eadie1, William E. Harris1, Aaron Springford2, Larry Widrow2

Institution(s): 1. McMaster University, 2. Queen's University

The mass and cumulative mass profile of the Milky Way's dark matter halo is a fundamental property of the Galaxy, and yet these quantities remain poorly constrained and span almost two orders of magnitude in the literature. There are a variety of methods to measure the mass of the Milky Way, and a common way to constrain the mass uses kinematic information of satellite objects (e.g. globular clusters) orbiting the Galaxy. One reason precise estimates of the mass and mass profile remain elusive is that the kinematic data of the globular clusters are incomplete; for some both line-of-sight and proper motion measurements are available (i.e. complete data), and for others there are only line-of-sight velocities (i.e. incomplete data). Furthermore, some proper motion measurements suffer from large measurement uncertainties, and these uncertainties can be difficult to take into account because they propagate in complicated ways. Past methods have dealt with incomplete data by using either only the line-of-sight measurements (and throwing away the proper motions), or only using the complete data. In either case, valuable information is not included in the analysis. During my PhD research, I have been developing a coherent hierarchical Bayesian method to estimate the mass and mass profile of the Galaxy that 1) includes both complete and incomplete kinematic data simultaneously in the analysis, and 2) includes measurement uncertainties in a meaningful way. In this presentation, I will introduce our approach in a way that is accessible and clear, and will also present our estimates of the Milky Way's total mass and mass profile using all available kinematic data from the globular cluster population of the Galaxy.