Resolving the Galactic Center Black Hole with the Event Horizon Telescope

Event Date:
2022-10-03T15:00:00
2022-10-03T16:00:00
Event Location:
HENNINGS Room 318
Speaker:
Chi-kwan Chan (University of Arizona / Steward Observatory)
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Intended Audience:
Undergraduate
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Abstract: In 2017, the Event Horizon Telescope (EHT) observed the Galactic Center supermassive black hole Sagittarius A* (Sgr A*) using a global interferometric array of 8 telescopes.  The resulting horizon scale images provide a unique opportunity to constrain the astrophysics of the accreting plasma and to test Einstein's general theory of relativity in a strong field regime.  In this talk, I will introduce the EHT project and go over its data processing pathway and imaging methods.  By comparing EHT's images with a large black hole simulation library, we constrain the properties of the accretion flow around Sgr A*.  By comparing the size of the observed photon ring with the predicted size of the shadow, we show that EHT's observations are consistent with general relativity.

Bio:

Chi-kwan Chan (CK) is an Associate Astronomer/Research Professor at Steward Observatory and the Department of Astronomy, University of Arizona, and has been serving as the Secretary of the Event Horizon Telescope (EHT) Science Council since 2020. He recently led the publication of the computational and theoretical modeling/interpretation of our black hole, Sgr A*. Dr. Chan created EHT’s computational and data processing infrastructure and continues to lead it to this day, along with EHT’s Software and Data Compatibility Working Group. He is a Senior Investigator of Black Hole PIRE, a leader of the Theoretical Astrophysics Program TAP, a Data Science Fellow, and a member of the Applied Mathematics Program. In addition to pioneering the use of GPU to accelerate the modeling of black holes, Dr. Chan also developed many new algorithms to improve and accelerate modern research, built cloud computing infrastructures for large observational data, and applied machine learning algorithms to speed up and automate data processing. Dr. Chan has taught and mentored in subjects of machine learning, numerical analysis, cloud computing, and quantum computing, and is an avid hiker.
 

Add to Calendar 2022-10-03T15:00:00 2022-10-03T16:00:00 Resolving the Galactic Center Black Hole with the Event Horizon Telescope Event Information:   Abstract: In 2017, the Event Horizon Telescope (EHT) observed the Galactic Center supermassive black hole Sagittarius A* (Sgr A*) using a global interferometric array of 8 telescopes.  The resulting horizon scale images provide a unique opportunity to constrain the astrophysics of the accreting plasma and to test Einstein's general theory of relativity in a strong field regime.  In this talk, I will introduce the EHT project and go over its data processing pathway and imaging methods.  By comparing EHT's images with a large black hole simulation library, we constrain the properties of the accretion flow around Sgr A*.  By comparing the size of the observed photon ring with the predicted size of the shadow, we show that EHT's observations are consistent with general relativity. Bio: Chi-kwan Chan (CK) is an Associate Astronomer/Research Professor at Steward Observatory and the Department of Astronomy, University of Arizona, and has been serving as the Secretary of the Event Horizon Telescope (EHT) Science Council since 2020. He recently led the publication of the computational and theoretical modeling/interpretation of our black hole, Sgr A*. Dr. Chan created EHT’s computational and data processing infrastructure and continues to lead it to this day, along with EHT’s Software and Data Compatibility Working Group. He is a Senior Investigator of Black Hole PIRE, a leader of the Theoretical Astrophysics Program TAP, a Data Science Fellow, and a member of the Applied Mathematics Program. In addition to pioneering the use of GPU to accelerate the modeling of black holes, Dr. Chan also developed many new algorithms to improve and accelerate modern research, built cloud computing infrastructures for large observational data, and applied machine learning algorithms to speed up and automate data processing. Dr. Chan has taught and mentored in subjects of machine learning, numerical analysis, cloud computing, and quantum computing, and is an avid hiker.   Event Location: HENNINGS Room 318