The mass distribution of the Milky Way (MW) has been the subject of a considerable amount of research, and yet many of its properties remain poorly constrained. We have developed two novel methods for understanding the properties of this mass distribution. The first involves using hydrodynamical simulations of the formation of the Magellanic Stream (MS), and compares the simulated streams to the observations of the MS. This comparison allows for a mass estimate of the MW because the properties of the simulated streams are sensitive to the MW mass assumed within the simulations. The second approach uses recent direct acceleration measurements, coupled with dynamical constraints from stellar streams, to constrain models of the MW's gravitational potential. Measuring accelerations of nearby stars is the most direct way to study the MW potential. However, the acceleration signals are small and currently are only detectable in the solar neighborhood. We use dynamical methods to understand the potential at larger distances and the accelerations at smaller distances. Our research has also focused on measuring the Hubble constant using time delays in strong lensing systems. First, we conducted a targeted difference imaging survey monitoring a sample of 114 known strong lensing systems, with the goal of detecting a lensed supernova in one of these systems. Although our two-year survey did not produce a detection of one of these rare events, it did give us valuable information about how to find lensed supernovae effectively in the future. Following this, we switched to simulating the effects of stars in the lensing galaxies on strongly lensed supernovae. We use these simulations to study methods to avoid contamination in our time delay measurements from the microlensing effects of these stars. The result is a new method for measuring time delays in strong lensing systems using lensed Type II-P supernovae.
Library of Congress Subject Headings
Milky Way--Computer simulation; Microlensing (Astrophysics); Supernovae; Cosmology
Astrophysical Sciences and Technology (Ph.D.)
Department, Program, or Center
School of Physics and Astronomy (COS)
Craig, Peter A., "Examining the Universe with Galaxies: From Dynamical Models to the Inference of Cosmological Parameters" (2023). Thesis. Rochester Institute of Technology. Accessed from
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