ASTRONOMY COLLOQUIUM

Machine Learning: The Evolution of Gas from Molecular Clouds to Stars

Stella Offner, Associate Professor of Astronomy, Center for Scientific Machine Learning, University of Texas, Austin,

Star formation results from a complex, non-linear interplay between gravity, turbulence, magnetic fields, radiation and stellar feedback. Machine learning, combined with numerical simulations, can effectively cut through the messiness of observational and simulation data to provide insights into the underlying physical behavior. I will describe three recent studies that apply supervised and unsupervised machine learning methods to tackle fundamental star formation questions: What is the distribution and impact of stellar feedback in molecular clouds? How does dense gas become star-forming? What is the future evolution of star-forming regions?

Event Sponsors:

Division of Physics, Mathematics and Astronomy - More events from this Sponsor

For more information, please contact Jim Fuller by email at [email protected] or visit https://www.astro.caltech.edu.