Presentation #105.02 in the session Molecular Clouds and the ISM — iPoster Session.
Massive stars emit a large amount of ultraviolet radiation that ionizes their immediate environments. The interplay between these stars and the ambient media surrounding them is important for understanding galactic evolution, but is poorly understood at small scales. To aid in our understanding of small-scale feedback, we present radio observations of Cygnus X, a nearby, highly-active star-formation region that has an enormous population of massive stars and therefore of ionized gas. Because of its proximity and the large angular size of its ionized regions, Cygnus X allows for observations of the morphology and dynamics of these environments at excellent angular resolution. We characterize these environments using radio recombination line (RRL) emission observations from a large (~60 hours) survey using the Green Bank Telescope, supplemented by data from previous radio and infrared surveys. We decompose the RRL emission into discrete components using GaussPy+, a Python machine learning algorithm for fitting Gaussian emission features, and analyze the distributions of intensities, velocity dispersions, and bulk velocities of the ionized gas.