Asteroseismology allows us to determine the properties of stars through the observation of their global oscillations, giving us information about the star’s mass, radius, and age. Beyond being interesting in their own right, these measurements are also essential for a variety of endeavors throughout astrophysics, such as galactic archaeology and the characterization of exoplanets. For the stars with the best observations, it is possible to additionally measure aspects of the internal stellar structure, which presents the opportunity of testing the physics of stellar evolution and probing far-ranging physics. These can range from searching for evidence of past binary interactions to constraining cosmological effects such as modified gravity and even shedding light on the problem of dark matter. In this seminar, I will give an overview of asteroseismology and highlight how machine learning applied to big theoretical and observational asteroseismic data sets is driving progress throughout astrophysics.
