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The mass of the Milky Way from satellite dynamics
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The mass of the Milky Way from satellite dynamics
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We present and apply a method to infer the mass of the Milky Way (MW) by comparing the dynamics of MW satellites to those of model satellites in the EAGLE cosmological hydrodynamics simulations. A distribution function (DF) for galactic satellites is constructed from EAGLE using specific angular momentum and specific energy, which are scaled so as to be independent of host halo mass. In this 2-dimensional space, the orbital properties of satellite galaxies vary according to the host halo mass. The halo mass can be inferred by calculating the likelihood that the observed satellite population is drawn from this DF. Our method is robustly calibrated on mock EAGLE systems. We validate it by applying it to the completely independent suite of 30 AURIGA high-resolution simulations of MW-like galaxies: the method accurately recovers their true mass and associated uncertainties. We then apply it to ten classical satellites of the MW with 6D phase-space measurements, including updated proper motions from the GAIA satellite. The mass of the MW is estimated to be $M_{200}^{\textnormal{MW}}=1.17_{-0.15}^{+0.21}\times10^{12}M_{\odot}$ (68\% confidence limits). We combine our total mass estimate with recent mass estimates in the inner regions of the Galaxy to infer an inner dark matter (DM) mass fraction $M^\textnormal{DM}(<20~\rm{kpc})/M^\textnormal{DM}_{200}=0.12$ which is typical of ${\sim}10^{12}M_{\odot}$ $\Lambda$CDM haloes in hydrodynamical galaxy formation simulations. Assuming an NFW profile, this is equivalent to a halo concentration of $c_{200}^{\textnormal{MW}}=10.9^{+2.6}_{-2.0}$.
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Cited by 1 Pith paper
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Tighter Dark Matter Constraints from the Projected Mass Method: A Neural Network Enhanced Method for Galaxy Groups and Clusters
A simulation-trained neural network removes most of the systematic overestimate of the Projected Mass Estimator, yielding Milky Way, M81, and NGC 5128 halo masses in line with the literature.
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