Data Sciences Speaker Series: Capturing the First Portrait of Our Milky Way’s Black Hole & Beyond – Katie Bouman

Session Description

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Professor Katie Bouman, from the Department of Computing and Mathematical Sciences, Caltech University, joins the Data Sciences Speaker Series (DSSS).

The DSSS is intended as a collaborative marquee series, whose focus is data science and its intersection with other fields. Together, we seek to advance knowledge in the field of data science by featuring world-class speakers from academic, healthcare, industry, finance, technology, and other sectors and industries. In doing so, we hope to facilitate the exchange of ideas, information, and knowledge among researchers, practitioners, and other professionals, and to enhance educational opportunities for students and trainees.

This talk is co-sponsored by the Data Sciences Institute and the Ontario Regional Centre of the Canadian Statistical Sciences Institute (CANSSI Ontario) at the University of Toronto.

• Date: Monday, November 21,2022
• Time: 12 pm – 1 pm EDT
• Format: Virtual

Title: Capturing the First Portrait of Our Milky Way’s Black Hole & Beyond

Abstract: This talk will present the methods and procedures used to produce the first image of Sagittarius A* — the black hole at the heart of the Milky Way galaxy. It has been theorized for decades that a black hole will leave a “shadow” on a background of hot gas. Taking a picture of this black hole shadow could help to address a number of important scientific questions, both on the nature of black holes and the validity of general relativity. Unfortunately, due to its small size, traditional imaging approaches require an Earth-sized radio telescope. In this talk, I discuss techniques we have developed to photograph the M87* and Sagittarius A* black holes using the Event Horizon Telescope, a network of telescopes scattered across the globe. Imaging Sagittarius A* proved even more challenging than M87*, due to the time-variability and interstellar scattering that had to be accounted for. I will summarize how the data from the 2017 observations were imaged and highlight the challenges that had to be addressed in order to capture an image of Sagittarius A*, including newly developed methods we used to characterize the morphology and uncertainty. Although we have learned a lot from these images already, remaining scientific questions motivate us to improve this computational telescope to see black hole phenomena still invisible to us. This talk will also discuss how we are developing techniques that will allow us to extract the evolving structure of our own Milky Way’s black hole over the course of a night in the future, perhaps even in three dimensions.

Bio: Katherine L. (Katie) Bouman is an assistant professor in the Computing and Mathematical Sciences, Electrical Engineering, and Astronomy Departments at the California Institute of Technology. Before joining Caltech, she was a postdoctoral fellow in the Harvard-Smithsonian Center for Astrophysics. She received her Ph.D. 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, and co-recipient of the Breakthrough Prize in Fundamental Physics. As part of the Event Horizon Telescope Collaboration, she is co-lead of the Imaging Working Group and acted as coordinator for papers concerning the first imaging of the M87* and Sagittarius A* black holes.

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