Search for: All records

ABSTRACT We provide new constraints on the dark matter halo density profile of Milky Way (MW) dwarf spheroidal galaxies (dSphs) using the phase-space distribution function (DF) method. After assessing the systematics of the approach against mock data from the Gaia Challenge project, we apply the DF analysis to the entire kinematic sample of well-measured MW dwarf satellites for the first time. Contrary to previous findings for some of these objects, we find that the DF analysis yields results consistent with the standard Jeans analysis. In particular, in this study we rediscover (i) a large diversity in the inner halo densities of dSphs (bracketed by Draco and Fornax), and (ii) an anticorrelation between inner halo density and pericenter distance of the bright MW satellites. Regardless of the strength of the anticorrelation, we find that the distribution of these satellites in density versus pericenter space is inconsistent with the results of the high-resolution N-body simulations that include a disc potential. Our analysis motivates further studies on the role of internal feedback and dark matter microphysics in these dSphs. 

ABSTRACT We analyse strongly lensed images in eight galaxy clusters to measure their dark matter density profiles in the radial region between 10 kpc and 150 kpc, and use this to constrain the self-interaction cross-section of dark matter (DM) particles. We infer the mass profiles of the central DM haloes, bright central galaxies, key member galaxies, and DM subhaloes for the member galaxies for all eight clusters using the qlens code. The inferred DM halo surface densities are fit to a self-interacting dark matter model, which allows us to constrain the self-interaction cross-section over mass σ/m. When our full method is applied to mock data generated from two clusters in the Illustris-TNG simulation, we find results consistent with no dark matter self-interactions as expected. For the eight observed clusters with average relative velocities of $$1458_{-81}^{+80}$$ km s−1, we infer $$\sigma /m = 0.082_{-0.021}^{+0.027} \rm cm^2\, g^{ -1}$$ and $$\sigma /m \lt 0.13~ \rm cm^2\, g^{ -1}$$ at the 95 per cent confidence level.