This theoretical work investigates hierarchical galaxy formation, using Andromeda (M31) galaxy and its streams and satellite galaxies as a test case. The close-by barred-spiral Andromeda galaxy is the only large galaxy in addition the Milky Way for which detailed measurements of the kinematics and elemental abundance of numerous individual stars can be obtained reasonably well. Here comprehensive modeling of M31's halo is done by constructing simulation-based dynamical models for each of the major halo components. The structure of the galaxy's halo is the result of the hierarchical assembly process of galaxies and the interpretation of the observations can be done by through numerical simulations of the formation process. The importance to know about the M31 halo is that this helps to better understand the building blocks, buildup history, and dark halo properties of spiral galaxies in general.
Major goals here are to constrain the mass profile of Andromeda's halo and the shape of its gravitational potential by using N-body simulations to model the dynamics for the large satellites of Andromeda, including the M31 Giant Stellar Stream (GSS), M33, M32, and NGC 205. The dynamical models are compared to large photometric data sets and velocity measurements to reconstruct the formation of halo streams. Bayesian methods are used to go beyond the construction of plausible individual models to quantified model uncertainties, parameter correlations, and objective comparisons of different models. Once the most prominent components have been modeled, the team plans to generate a description of the remaining, more fully mixed smooth halo component. These results will check the current observational evidence that M31, like the Milky Way, is an apparent outlier in the cosmic stellar mass/halo mass relation.
The results of this research will have impact on a wide range of astrophysical research, as it concerns the structure of ubiquitous dark matter haloes. The model results are distributed in a public database, and a website will provide simulations and visualizations of models from this project. The research provides good projects for graduate and undergraduate students, which helps to train the next generation of scientists.
