Kavli Affiliate: Lina Necib
| First 5 Authors: Laura J. Chang, Lina Necib, , ,
| Summary:
The distribution of dark matter in dwarf galaxies can have important
implications on our understanding of galaxy formation as well as the particle
physics properties of dark matter. However, accurately characterizing the dark
matter content of dwarf galaxies is challenging due to limited data and complex
dynamics that are difficult to accurately model. In this paper, we apply
spherical Jeans modeling to simulated stellar kinematic data of spherical,
isotropic dwarf galaxies with the goal of identifying the future observational
directions that can improve the accuracy of the inferred dark matter
distributions in the Milky Way dwarf galaxies. We explore how the dark matter
inference is affected by the location and number of observed stars as well as
the line-of-sight velocity measurement errors. We use mock observation to
demonstrate the difficulty in constraining the inner core/cusp of the dark
matter distribution with datasets of fewer than 10,000 stars. We also
demonstrate the need for additional measurements to make robust estimates of
the expected dark matter annihilation signal strength. For the purpose of
deriving robust indirect detection constraints, we identify Ursa Major II, Ursa
Minor, and Draco as the systems that would most benefit from additional stars
being observed.
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