The first picture of a black hole is a huge day for science. However, it's an even bigger day for all the women in science around the world.
That's because though it was 200-odd researchers working to image the black hole, it all happened because of one woman.
TED.com
The research group used the Event Horizon Telescope to observe the black hole. Because of the size of the object involved, they needed a telescope with an angular resolution the same size as its event horizon.
To do that, the team combined data from eight radio telescopes across the world into one image. That's not an easy task, given that each of these was producing about 350TB of data each day. The process had to be automated of course, and that's where Katie Bouman comes in.
An MIT graduate, Bouman's expertise is not in astrophysics but in computer science. In college, she developed an algorithm designed to work with vast amounts of data. And along with a team of three others, Bouman tweaked the program to work for the gigantic EHT project, collating the data and filtering out the noise to give us the breathtaking fiery donut.
In fact, Bouman has seen a sudden surge of popularity in the public eye, thanks largely to social media. After all, women in STEM have often been brushed aside, even their achievements buried, in favour of giving credit to their male counterparts. In Bouman's case though, it's impossible to deny just how key her contributions were.
One photo of her is especially viral right now. On one half, it shows Bouman with her stacks of hard drives with data from the satellites. On the other, it shows an eerily similar much older photo, that of Margaret Hamilton with her paper stacks of code for the Apollo 11's guidance systems. Two women that made major contributions to humanity achieving path-breaking milestones.
Another popular photo online is one posted by Bouman herself, reacting to her program rendering the image of the black hole for the first time. That photo was actually taken way back in June last year, when the image was first computed. The team have had to keep silent about it until now, while they tested and verified their data and algorithm.
"Traditionally the way you make images in radio astronomy is you actually have a human there who is kind of guiding the imaging methods in the direction they think they should go," Bouman told Time. "And for data like this, that is so sparse, so noisy, where it's so hard to try to find an image, that was a dangerous game to play."