Goodbye fuzzy donut: The famous first black hole photo gets sharpened up
The first iconic image of a black hole looked like a fuzzy, orange donut, but now that picture has been sharpened up to a fiery ring, thanks to computer simulations and machine learning.
The black interior of this ring of hot gasses is an area of cosmic weirdness and such strong gravity that nothing, not even light, can escape. It looks much larger and darker in the upgraded image, according to a new report in The Astrophysical Journal Letters.
The picture shows the M87 black hole, a large one about 55 million light years away that's thought to be 6.5 billion times more massive than the sun. This is the black hole that was observed in 2017 by a network of telescopes around the world known as the Event Horizon Telescope, which together acted as a giant radio telescope the size of the Earth.
Two years later, with much fanfare, the international EHT team announced they'd produced the first image of M87. "We're very, very proud and we're really excited about that image. I was really involved in making that image," says astrophysicist Lia Medeiros of the Institute for Advanced Study in Princeton, N. J.
Even so, she says, "we're always going to be trying to improve and always going to be trying to have an ever-better image."
The idea of a celestial object with such strong gravity that it won't let light escape, rendering it invisible, has been around since the 18th century. Astronomers now know that black holes can form when a dying star collapses in on itself. Although the black hole itself can't be seen, its presence can be inferred from the effects of its gravity on its surroundings.
For example, the gas, dust, and debris that gets pulled into a black hole swirls around and heats up as it falls inward, creating an outline around the unseeable, insatiable beast. That outline is what the EHT team was able to capture.
But making a portrait of a black hole with an array of telescopes, Medeiros explains, is very different from snapping a photo with an everyday camera. "We don't really take a picture in the sense that, you know, there's just one camera that just goes click," she says.
Instead, the researchers have to deal with gaps in their data by making certain assumptions and doing a ton of calculations.
In this new version of the image, the gaps have been filled with the help of physics — namely, computer simulations of black holes — and machine learning. Researchers generated over 30,000 simulated images of black holes, covering a wide range of possibilities, and then looked for common patterns within those images.
"What we really do is we learn the correlations between different parts of the image. And so we do this by analyzing tens of thousands of high-resolution images that are created from simulations," says Medeiros. "If you have an image, the pixels close to any given pixel are not completely uncorrelated. It's not that each pixel is doing completely independent things."
Learning the correlations between the bits of the images helped them better fill in the gaps created by missing data, she says. And the resulting new image is consistent with the old one, but the ring of hot gasses swirling around the black hole is significantly thinner.
"The fact that the ring width is smaller by about a factor of two is incredibly exciting," says Medeiros.
It's a revelation that will help them understand what is happening as matter swirls around the black hole and falls in.
"If we have more matter falling into the black hole, it'll create a thicker ring. And if we have a smaller amount of matter falling in, it should create a thinner ring, right?" she says.
So far, everything still looks consistent with Albert Einstein's predictions. That's also true for the only other black hole to have been imaged, the one at the center of the Milky Way galaxy. It was also observed by this research consortium.
Medeiros thinks that continued improvements in computer software and telescope hardware will result in the picture of the M87 black hole being refined more and more.
"In 20 years, the image might not be the image I'm showing you today," she says. "It might be even better."
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