Remember how we got to see the supermassive black hole in the movie Interstellar? Well, that wasn’t for real. We know that black holes end up sucking everything that’s too close to it, even light for that matter. Black hole’s event horizon cast a shadow and that shadow is enough for answering a lot of questions attached to black hole theory. And scientists and researchers have been working towards it since years to get that one image to give an angle to their research.
And finally comes the biggest news that a team of astronomers, engineers, researchers and scientists have managed to capture the first ever image of a black hole, which is located in a distant galaxy. It is three million times the size of the Earth and it measures 40 billion Km across. The team describes it as “a monster” and was photographed by a network of eight telescopes across the world.
In this article, we give you a glimpse of how did the image of the black hole got captured? Katie Bouman, a PhD student at MIT appeared at TED Talks and discussed the efforts taken by the team of researchers, engineers, astronomers and scientists to capture the first ever image of the black hole. Katie is a part of an international team of astronomers who worked for creating the world’s largest telescope, Event Horizon Telescope to click the first ever picture of the black hole. She led the development of a computer programme that made this impossible, possible! She started working on the algorithm three years ago while she was a graduate student.
Her name is Katie Bouman, an MIT graduate.
— Jen Zhu (@jenzhuscott) April 10, 2019
Katie wrote in the caption to one of the Facebook post, “Watching in disbelief as the first image I ever made of a black hole was in the process of being reconstructed.”
Scientist Katie Bouman just posted about the moment when "the first image I ever made of a black hole" was processed.
— MIT CSAIL (@MIT_CSAIL) April 10, 2019
Further, she explains how the stars we see in the sky basically orbit an invisible object. And according to the astronomers, the only thing that can cause this motion of the stars is a supermassive black hole.
Zooming in at radio wavelengths to see a ring of light
“Well, it turns out that if we were to zoom in at radio wavelengths, we’d expect to see a ring of light caused by the gravitational lensing of hot plasma zipping around the black hole. Is it possible to see something that, by definition, is impossible to see? ” -Katie Bouman
If we closely look at it, we can see that the black hole casts a shadow on the backdrop of bright material that carves out a sphere of darkness. It is a bright ring that reveals the black hole’s event horizon, where the gravitational pull becomes so powerful that even light can’t escape. Einstein’s equations have predicted the size and shape of this ring and taking a picture of it would help to verify that these equations hold in the extreme conditions around the black hole.
Capturing black hole needs a telescope the size of the Earth
“So how big of a telescope do we need in order to see an orange on the surface of the moon and, by extension, our black hole? Well, it turns out that by crunching the numbers, you can easily calculate that we would need a telescope the size of the entire Earth.” -Katie Bouman
Bouman further explains that black hole is so far away from Earth that this ring appears incredibly small, as small as an orange on the surface of the moon. And this makes it difficult to capture the photo of the black hole. There are fundamental limits to the smallest objects that we can see because of diffraction. So the astronomers realized that they need to make their telescope bigger and bigger. Even the most powerful optical telescopes couldn’t get close to the resolution necessary to image on the surface of the moon. She showed one of the highest resolution images ever taken of the moon from Earth to the audience which contained around 13,000 pixels, and each pixel contained over 1.5 million oranges.
Capturing the black hole turned into reality by connecting telescopes
“And so, my role in helping to take the first image of a black hole is to design algorithms that find the most reasonable image that also fits the telescope measurements.” -Katie Bouman
According to Bouman, we would require a telescope as big as earth’s size to see an orange on the surface of the moon. Capturing a black hole seemed to be imaginary back then as it was nearly impossible to have a powerful telescope. Bouman highlighted the famous words of Mick Jagger, “You can’t always get what you want, but if you try sometimes, you just might find you get what you need.”
Capturing the black hole turned into a reality by connecting telescopes from around the world. Event Horizon Telescope, an international collaboration created a computational telescope the size of the Earth which was capable of resolving structure on the scale of a black hole’s event horizon. The setup was such that each telescope in the worldwide network worked together. The researcher teams at each of the sites collected thousands of terabytes of data. This data then processed in a lab in Massachusetts.
Let’s understand this in depth by assuming that we can build an Earth sized telescope! Further imagining that Earth is a spinning disco ball and each of the mirror of the ball can collect light that can be combined together to form a picture. If most of those mirrors are removed then a few will remain. In this case, it is still possible to combine this information together, but now there will be a lot of holes. The remaining mirrors represent the locations where these telescopes have been setup. Though this seems like a small number of measurements to make a picture from but it is effective. The light gets collected at a few telescope locations but as the Earth rotates, other new measurements also get explored.
So, as the disco ball spins, the mirrors change locations and the astronomers get to observe different parts of the image. The imaging algorithms developed by the experts, scientists and researchers fill in the missing gaps of the disco ball in order to reconstruct the underlying black hole image.
Katie Bouman said, “If we had telescopes located everywhere on the globe — in other words, the entire disco ball — this would be trivial. However, we only see a few samples, and for that reason, there are an infinite number of possible images that are perfectly consistent with our telescope measurements.”
According to Bouman, not all the images are created equal. So some of those images look more like what the astronomers, scientists and researchers think of as images as compared to others.
Bouman’s role in helping to take the first image of the black hole was to design the algorithms that find the most relevant or reasonable image that fits the telescope measurements. The imaging algorithms developed by Katie used the limited telescope data to guide the astronomers to a picture. With the help of these algorithms, it was possible to bring together the pieces of pictures from the sparse and noisy data.
How was the algorithm used in creation of the black hole image
“I’d like to encourage all of you to go out and help push the boundaries of science, even if it may at first seem as mysterious to you as a black hole.” -Katie Bouman
There is an infinite number of possible images that perfectly explain the telescope measurements and the astronomers and researchers have to choose between them. This is possible by ranking the images based upon how likely they are to be the black hole image and further selecting the one that’s most likely.
Bouman explained it with the help of an example, “Let’s say we were trying to make a model that told us how likely an image were to appear on Facebook. We’d probably want the model to say it’s pretty unlikely that someone would post this noise image on the left, and pretty likely that someone would post a selfie like this one on the right. The image in the middle is blurry, so even though it’s more likely we’d see it on Facebook compared to the noise image, it’s probably less likely we’d see it compared to the selfie.”
While talking about the images from the black hole, according to Katie it gets confusing for the astronomers and researchers as they have never seen a black hole before. She further explained how difficult it is to rely on any of the previous theories for these images. It is even difficult to completely rely on the images of the simulations for comparison.
She said, “What is a likely black hole image, and what should we assume about the structure of black holes? We could try to use images from simulations we’ve done, like the image of the black hole from “Interstellar,” but if we did this, it could cause some serious problems. What would happen if Einstein’s theories didn’t hold? We’d still want to reconstruct an accurate picture of what was going on. If we bake Einstein’s equations too much into our algorithms, we’ll just end up seeing what we expect to see. In other words, we want to leave the option open for there being a giant elephant at the center of our galaxy.”
According to Bouman, different types of images have distinct features, so it is quite possible to identify the difference between black hole simulation images and images captured by the team. So the researchers need to let the algorithms know what images look like without imposing one type of image features. And this can be done by imposing the features of different kinds of images and then looking at how the image type we assumed affects the reconstruction of the final image. The researchers and astronomers become more confident about their image assumptions if the images’ types produce a very similar-looking image.
She said, “This is a little bit like giving the same description to three different sketch artists from all around the world. If they all produce a very similar-looking face, then we can start to become confident that they’re not imposing their own cultural biases on the drawings.”
It is possible to impose different image features by using pieces of existing images. So the astronomers and researchers took a large collection of images and broke them down into little image patches. And then they treated each image patch like piece of a puzzle. They use commonly seen puzzle pieces to piece together an image that also fits in their telescope measurements.
She said, “Let’s first start with black hole image simulation puzzle pieces. OK, this looks reasonable. This looks like what we expect a black hole to look like. But did we just get it because we just fed it little pieces of black hole simulation images?”
If we take a set of puzzle pieces from everyday images, like the ones we take with our own personal camera then we get the same image from all different sets of puzzle pieces. And we then become more confident that the image assumptions made by us aren’t biasing the final image.
According to Bouman, another thing that can be done is take the same set of puzzle pieces like the ones derived from everyday images and then use them to reconstruct different kinds of source images.
Bouman said, “So in our simulations, we pretend a black hole looks like astronomical non-black hole objects, as well as everyday images like the elephant in the center of our galaxy.”
And when the results of the algorithms look very similar to the simulated image then researchers and astronomers become more confident about their algorithms.
She emphasized that all of these pictures were created by piecing together little pieces of everyday photographs, like the ones we take with own personal camera. So an image of a black hole which we have never seen before can be created by piecing together pictures we see regularly like images of people, buildings, trees, cats and dogs.
She concluded by appreciating the efforts taken by her team, “But of course, getting imaging ideas like this working would never have been possible without the amazing team of researchers that I have the privilege to work with. It still amazes me that although I began this project with no background in astrophysics. But big projects like the Event Horizon Telescope are successful due to all the interdisciplinary expertise different people bring to the table.”
This project will surely encourage many researchers, engineers, astronomers and students who are under dark and not confident of themselves but have the potential to make the impossible, possible.
One thing planetary physics taught me: you can avoid crashing into massive problems if you just keep circling around them really fast
— François Chollet (@fchollet) April 11, 2019