Factual (United States)

We use cosmological simulations of isolated Milky Way-mass galaxies, as well as Local Group analogues, to define the "edge" -- a caustic manifested in a drop in density or radial velocity -- of Galactic-sized haloes, both in dark matter and in stars. In the dark matter, we typically identify two caustics: the outermost caustic located at ~1.4r_200m corresponding to the "splashback" radius, and a second caustic located at ~0.6r_200m which likely corresponds to the edge of the virialized material which has completed at least two pericentric passages. The splashback radius is ill defined in Local Group type environments where the halos of the two galaxies overlap. However, the second caustic is less affected by the presence of a companion, and is a more useful definition for the boundary of the Milky Way halo. Curiously, the stellar distribution also has a clearly defined caustic, which, in most cases, coincides with the second caustic of the dark matter. This can be identified in both radial density and radial velocity profiles, and should be measurable in future observational programmes. Finally, we show that the second caustic can also be identified in the phase-space distribution of dwarf galaxies in the Local Group. Using the current dwarf galaxy population, we predict the edge of the Milky Way halo to be 292 +/- 61 kpc.

Although to-do lists are a ubiquitous form of personal task management, there has been no work on intelligent assistance to automate, elaborate, or coordinate a user’s to-dos. Our research focuses on three aspects of intelligent assistance for to-dos. We investigated the use of intelligent agents to automate to-dos in an office setting. We collected a large corpus from users and developed a paraphrase-based approach to matching agent capabilities with to-dos. We also investigated to-dos for personal tasks and the kinds of assistance that can be offered to users by elaborating on them on the basis of substep knowledge extracted from the Web. Finally, we explored coordination of user tasks with other users through a to-do management application deployed in a popular social networking site. We discuss the emergence of Social Task Networks, which link users‘ tasks to their social network as well as to relevant resources on the Web. We show the benefits of using common sense knowledge to interpret and elaborate to-dos. Conversely, we also show that to-do lists are a valuable way to create repositories of common sense knowledge about tasks.