Rutgers University Astrophysics Seminar
The 3D structure of the Milky Way and its molecular clouds
The detailed 3D distributions of dust density and extinction in the Milky Way have long been sought after. However, such 3D reconstruction from sparse data is non-trivial, but is essential to understanding the properties of star-formation, large-scale dynamics and structure of our Galaxy. In this work I will introduce our new fast and scalable algorithm for 3D dust modeling. Using advanced ML methods such as sparse Gaussian Processes and Variational Inference, our algorithm maps the Solar Neighbourhood with millions of input sources in parsec scales within short timescales. Using this approach we map the inner 3 kpc of the Solar Neighbourhood down to 1 pc resolution.We identify large-scale structures in the Galaxy and its Molecular clouds, while simultaneously peering into individual molecular clouds. I will introduce our newly discovered Eos molecular cloud which is the nearest molecular cloud to earth discovered for the first time in UV fluorescence. The Eos cloud consists of 98% CO-dark gas, providing evidence for the missing mass needed to fuel star formation, as theory predicts over 50% of the total mass required remains unobserved.