Learning how Stars Form: Harnessing AI to Identify Structures in Noisy Spectral Cubes
Star formation is messy! The process spans many orders of magnitude in scale and involves a variety of physical processes: gravity, magnetic fields, radiation, and turbulence. Young stars announce their presence by emitting radiation and ejecting high-velocity material, “stellar feedback,” which in turn shapes the surrounding natal environment.
Dr. Stella Offner presents results from a 3-D convolutional neural network model trained on full-physics numerical simulations that accurately identify stellar feedback features in molecular line spectral cubes. She discusses the pros and cons of supervised approaches based on numerical simulations for data segmentation.