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How does EHT work?
How do we recover a single image?
Regularized Maximum Likelihood Problem
Sampling from a Posterior Distribution Using a Generative Neural Network
Results on M87 Data
How to get the range of Sag A* appearances?
Event Horizon Telescope Data
Expanding the Event Horizon Telescope Array
Closing Remarks
What is a supermassive black hole?
How do we make a picture from disjoint telescopes?
Why does VLBI break down?
What is the disadvantage of this method?
How do you avoid biasing your images?
How did you approach the M87 data?
EHT Imaging & Smiley
Extracting Parameters
What are the differences between M87 and Sag A*?
Can we see other black holes?
Meet the scientist who made the first-ever image of a black hole possible
Bouman is a computational imaging expert
Getting this first picture will come down to an international team
The EHT project's 8 telescopes are placed on 5 continents
In a 2016 TEDTalk
EHT's computer scientists were tasked with creating algorithms to fill the holes
The EHT team split its imaging experts into 4 different teams
The teams used their respective algorithms to analyze data
The ring surrounding the black hole is a collection of chaotic photons
The black hole has 6.5 billion times the mass of our sun
What happens if we zoom in even further?
The diffraction limit
Highest resolution image of the moon
Event Horizon Telescope
How does Event Horizon Telescope work?
How does it work?
Imposing different image features
What happens when we use different sets of puzzle pieces?
Reconstructing different kinds of source images
Interdisciplinary expertise
Intro
Regularized Maximum Likelihood Estimation
Transferring parameters from synthetic to real data
Learned Generative Neural Networks
Regularized Maximum Likelihood methods
The Story of M87
What are the different approaches to recovering the underlying motion of a source?
Non-Isotropic Diffusion
Conclusion
Acknowledgements
Imaging the Invisible
How does Event Horizon Telescope work?
How do we verify what we're reconstructing with our imaging algorithms?
M87 image variations
Learning generative neural networks
How does it work?
Is the recovered image moving?
Synthetic ground-truth video
Computing the projection of the random field onto the subspace
Closing Remarks