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This effort would not have been possible without Katie Bouman, who developed a crucial algorithm that helped design imaging methods.
Black holes are extremely distant and compact, so it is difficult to take a picture of any of them. In addition, black holes, by definition, are supposed to be invisible – though they can clear a shadow they interact with the material around them.
A global network of telescopes known as the Horizon Telescope Event Project has collected millions of gigabytes of data on M87 using a technique called interferometry. However, there were still major gaps in the data to be completed.
Its algorithm, and many others, have made it possible to fill the gaps
It is there that intervenes the Bouman algorithm, as well as several others. Using imaging algorithms like that of Bouman, the researchers created three scripted code pipelines to reconstruct the image.
They took "sparse and noisy data" that the telescopes spat and tried to create an image. For a few years, Bouman has been managing the image verification and the selection of imaging parameters.
"We developed ways to generate synthetic data and used different algorithms, and we blindly tested whether we could recover an image," she told CNN.
"We did not want to develop a single algorithm, we wanted to develop many different algorithms that all have different badumptions, and if all of them get the same overall structure, that boosts your confidence."
The result? Revolutionary image of a ring structure, unbalanced, that Albert Einstein had predicted more than a century ago in his theory of general relativity. In fact, the researchers had generated several photos and they were all alike. The image of the black hole presented Wednesday did not come from a single method, but from all the different images of algorithms that were fuzzy.
"No matter what we did, you'd have to go crazy to get something that was not that ring," Bouman said.
Bouman was a crucial member of the imaging team
"(Bouman) was an important part of one of the imaging subgroups," said Vincent Fish, a research scientist at MIT's Haystack Observatory.
"One of the ideas that Katie provided to our imaging group is that there are natural images," Fish said. "Just think of the photos you take with your camera phone.They have certain properties.If you know what a pixel is, you have a good idea of what the pixel is next."
For example, some areas are smoother and some areas are delineated accurately. The astronomical images share these properties and you can encode them mathematically, said Fish.
Junior members like Bouman made a significant contribution to the project, he added. Of course, experienced scientists worked on the project, but the imaging part was mainly run by young researchers, such as graduate students and post-docs.
"Nobody among us could have done it alone," Bouman said. "This has been done thanks to lots of different people from all walks of life."
Bouman begins teaching as an badistant professor at the California Institute of Technology in the fall.
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