MIT Graduate Student Katie Bauman Made The Black Hole Image Possible

    Katie Bauman Black hole image

    The black hole where all the secrets of the universe are hidden, image was revealed to the world. Many of the great scientists of the centuries who burned their midnight oil to study about the black hole might have not come to the end. But for now, the world is enthralled by the black hole image. Thanks to the MIT graduate student, Katie Bauman, a computer scientist shared the photo of her reacting to the image of a black hole processing in her computer

    The international team of more than 200 researchers unveiled the image of the first black hole and that wasn’t possible without Katie Bouman who developed a crucial algorithm that helped devise imaging methods. The MIT student named the algorithm CHIRP (Continuous High-resolution Image Reconstruction using Patch priors). CHIRP had to combine the data from the eight radio telescopes around the world, working under the Even Horizon Telescope that captured black hole image and turned into now known “M87” image.

    Katie Bauman created this incredible algorithm three years ago that captured the supermassive image. The researchers from MIT’s Computer Science and Artificial Intelligence Laboratory, the Harvard-Smithsonian Center for Astrophysics, and the MIT Haystack Observatory were involved in the project “to turn the entire planet into a large radio telescope dish.”

    It was difficult to extract the visual information as the radio telescope received astronomical signs at different that made the calculations not precise and hence visual information.

    “We developed ways to generate synthetic data and used different algorithms and tested blindly to see if we can recover an image,” Katie told CNN. We didn’t want to just develop one algorithm. We wanted to develop many different algorithms that all have different assumptions built into them. If all of them recover the same general structure, then that builds your confidence.”

    The image formed was the result of different imaging algorithms and they were together blurred out together. “No matter what we did, you would have to bend over backwards crazy to get something that wasn’t this ring,” Bouman said.

    “One of the insights Katie brought to our imaging group is that there are natural images,” Vincent Fish, a research scientist at MIT’s Haystack Observatory said. “Just think about the photos you take with your camera phone — they have certain properties. … If you know what one pixel is, you have a good guess as to what the pixel is next to it.”
    For example, there are areas that are smoother and areas that have sharp boundaries. Astronomical images share these properties, and you can mathematically encode these properties, Fish said.

    The junior member of the project majorly contributed to the imaging methods. “No one of us could’ve done it alone,” Bouman said. “It came together because of lots of different people from many backgrounds.” Katie Bauman starts teaching as an assistant professor at the California Institute of Technology in the fall. The data collected for the image had to be stored in a lot of hard drives


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