Details

At the heart of our Milky Way galaxy lies a supermassive black hole called Sagittarius A* that is evolving on the timescale of mere minutes. Computer scientist Katie Bouman will present the methods and procedures used to produce the first images of Sagittarius A* as well as discuss future directions we are taking to leverage machine learning to sharpen our view of the black hole, including mapping its evolving environment in 3D.

It has been theorized for decades that a black hole will leave a "shadow" on a background of hot gas. However, due to its small size, traditional imaging approaches require an Earth-sized radio telescope. In this talk, Bouman discusses techniques developed to photograph a black hole using the Event Horizon Telescope, a network of telescopes scattered across the globe. Recovering an image from this data requires solving an ill-posed inverse problem which necessitates the use of image priors to reduce the space of possible solutions. Although we have learned a lot from these initial images already, remaining scientific questions motivate us to improve this computational telescope to see black hole phenomena still invisible to us. She will discuss approaches developed to incorporate data-driven diffusion model priors into the imaging process to sharpen the view of the black hole and understand the sensitivity of the image to different underlying assumptions. Additionally, she will discuss how her team has developed techniques that allow them to extract the evolving structure of our own Milky Way’s black hole over the course of a night. She will introduce Orbital Black Hole Tomography, which integrates known physics with a neural representation to map evolving flaring emission around the black hole in 3D for the first time.

Speaker

Katherine L. (Katie) Bouman is a professor in the Computing and Mathematical Sciences, Electrical Engineering and Astronomy departments at the California Institute of Technology. Her work combines ideas from signal processing, computer vision, machine learning and physics to find and exploit hidden signals for scientific discovery. Before joining Caltech, she was a postdoctoral fellow in the Harvard-Smithsonian Center for Astrophysics. She received her PhD in the Computer Science and Artificial Intelligence Laboratory (CSAIL) at MIT in EECS, and her bachelor's degree in electrical engineering from the University of Michigan. She is a Rosenberg Scholar, Heritage Medical Research Institute Investigator, recipient of the Royal Photographic Society Progress Medal, Electronic Imaging Scientist of the Year Award, Sloan Fellowship, University of Michigan Outstanding Recent Alumni Award and co-recipient of the Breakthrough Prize in Fundamental Physics. As part of the Event Horizon Telescope Collaboration, she co-led the Imaging Working Group and acted as coordinator for papers concerning the first imaging of the M87* and Sagittarius A* black holes.