The Information Content in Cold Stellar Streams

Abstract

Abstract Cold stellar streams—produced by tidal disruptions of globular clusters—are long-lived, coherent dynamical features in the halo of the Milky Way. They hold the promise of delivering precise information about the gravitational potential, including constraints on the shape of the dark matter halo. Because of their different ages and different positions in phase space, different streams tell us different things about the Galaxy. Here we employ a Cramér–Rao lower bound (CRLB) or Fisher-matrix approach to understand the quantitative information content in (toy versions of) 11 known streams: ATLAS, GD-1, Hermus, Kwando, Orinoco, PS1A, PS1C, PS1D, PS1E, Sangarius, and Triangulum. This approach depends on a generative model, which we have developed previously, and which permits calculation of derivatives of predicted stream properties with respect to Galaxy and stream parameters. We find that in simple analytic models of the Milky Way, streams on eccentric orbits contain the most information about the halo shape. For each stream, there are near degeneracies between dark matter halo properties and parameters of the bulge, the disk, and the stream progenitor itself, but simultaneous fitting of multiple streams will constrain all parameters at the percent level. At this precision, simulated dark matter halos deviate from simple analytic parameterizations, so we add an expansion of basis functions as a first step in giving the gravitational potential more freedom. As freedom increases, the information about the halo reduces overall, and it becomes more localized to the current position of the stream. In the limit of high model freedom, a stellar stream appears to measure the local acceleration at its current position; this motivates thinking about future nonparametric approaches. The CRLB formalism also permits us to assess the value of future measurements of stellar velocities, distances, and proper motions. We show that velocities of stream stars are essential for producing competitive constraints on the distribution of dark matter.