Gaia’s sky in colour. Image via European Space Agency. Copyright information: ESA/Gaia/DPAC, CC BY-SA 3.0 IGO

Gaia’s sky in colour. Image via European Space Agency. Copyright information: ESA/Gaia/DPAC, CC BY-SA 3.0 IGO

Dr. Gwendolyn Eadie (eScience Institute, Data-Intensive Research in Astrophysics and Cosmology Institute, and Natural Sciences and Engineering Research Council of Canada postdoctoral fellow in the UW Department of Astronomy) is collaborating with Dr. Mario Juric (Astronomy Department and eScience senior data science fellow) and undergraduate Anika Slizewski to estimate the total mass of the galaxy using the latest data from the European Space Agency’s (ESA) Gaia Satellite. The mass of our galaxy is an important quantity for understanding the distribution and amount of mysterious dark matter in the Milky Way. It is also paramount for understanding our galaxy’s history and formation, and the Milky Way’s interaction with other galaxies and dwarf galaxies in the Local Group of Galaxies.

In 2018, ESA released the data and derived data products from the Gaia satellite, which included measurements of the positions and velocities of dense clusters of stars called globular clusters and the smaller dwarf galaxies that orbit the galaxy. Eadie and Juric have used the globular clusters in a hierarchical Bayesian analysis to estimate the total mass and cumulative mass profile of the Milky Way (published in The Astrophysical Journal, here). 

Some advantages of using the hierarchical Bayesian method is that it includes measurement uncertainties, allows for data that are incomplete, and produces results that can be used as valuable information in future studies. A Bayesian analysis produces a posterior distribution, which is a probability distribution of the model parameters of interest. This posterior distribution is a summary of the results, but it can also be for prediction, and quantifies the uncertainties with which those predictions are made. The posterior distribution, along with its uncertainties, is also easily carried forward to future studies when new data are collected. The study by Eadie and Juric resulted in such a posterior distribution for the model parameters describing the mass of the Milky Way, and this is now being used to inform the next study.

Currently, Slizewski, Juric, and Eadie are working with the dwarf galaxy data, in combination with the results from the study by Eadie and Juric, to obtain an even better estimate of the Milky Way’s mass. They are also exploring any possible effects of using the prior information from the Eadie and Juric study versus using little prior information.

The Gaia data have been transformative for how scientists study the Milky Way Galaxy, not only in terms of its mass but also in terms of its composition and structure. Nevertheless, it has been difficult to determine which model for the galaxy best describes its mass and its mysterious dark matter component. Thus, once their current study is complete, there will be many other avenues to pursue. In a future study, Eadie plans to lead a project that utilizes Bayesian model comparison, in hopes of discovering which physical model can best describe our galaxy given the data.