How to take a picture of a black hole
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0:01 - 0:03In the movie "Interstellar,"
-
0:03 - 0:07we get an up-close look
at a supermassive black hole. -
0:07 - 0:09Set against a backdrop of bright gas,
-
0:09 - 0:11the black hole's massive
gravitational pull -
0:11 - 0:12bends light into a ring.
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0:12 - 0:15However, this isn't a real photograph,
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0:15 - 0:16but a computer graphic rendering --
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0:16 - 0:20an artistic interpretation
of what a black hole might look like. -
0:20 - 0:22A hundred years ago,
-
0:22 - 0:25Albert Einstein first published
his theory of general relativity. -
0:25 - 0:27In the years since then,
-
0:27 - 0:30scientists have provided
a lot of evidence in support of it. -
0:30 - 0:33But one thing predicted
from this theory, black holes, -
0:33 - 0:35still have not been directly observed.
-
0:35 - 0:38Although we have some idea
as to what a black hole might look like, -
0:38 - 0:41we've never actually taken
a picture of one before. -
0:41 - 0:45However, you might be surprised to know
that that may soon change. -
0:45 - 0:50We may be seeing our first picture
of a black hole in the next couple years. -
0:50 - 0:54Getting this first picture will come down
to an international team of scientists, -
0:54 - 0:55an Earth-sized telescope
-
0:55 - 0:58and an algorithm that puts together
the final picture. -
0:58 - 1:02Although I won't be able to show you
a real picture of a black hole today, -
1:02 - 1:05I'd like to give you a brief glimpse
into the effort involved -
1:05 - 1:06in getting that first picture.
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1:07 - 1:09My name is Katie Bouman,
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1:09 - 1:12and I'm a PhD student at MIT.
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1:12 - 1:14I do research in a computer science lab
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1:14 - 1:17that works on making computers
see through images and video. -
1:17 - 1:19But although I'm not an astronomer,
-
1:19 - 1:20today I'd like to show you
-
1:20 - 1:23how I've been able to contribute
to this exciting project. -
1:23 - 1:26If you go out past
the bright city lights tonight, -
1:26 - 1:29you may just be lucky enough
to see a stunning view -
1:29 - 1:30of the Milky Way Galaxy.
-
1:30 - 1:33And if you could zoom past
millions of stars, -
1:33 - 1:3626,000 light-years toward the heart
of the spiraling Milky Way, -
1:36 - 1:40we'd eventually reach
a cluster of stars right at the center. -
1:40 - 1:43Peering past all the galactic dust
with infrared telescopes, -
1:43 - 1:47astronomers have watched these stars
for over 16 years. -
1:47 - 1:51But it's what they don't see
that is the most spectacular. -
1:51 - 1:54These stars seem to orbit
an invisible object. -
1:54 - 1:56By tracking the paths of these stars,
-
1:56 - 1:57astronomers have concluded
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1:57 - 2:01that the only thing small and heavy
enough to cause this motion -
2:01 - 2:03is a supermassive black hole --
-
2:03 - 2:07an object so dense that it sucks up
anything that ventures too close -- -
2:07 - 2:08even light.
-
2:08 - 2:11But what happens if we were
to zoom in even further? -
2:11 - 2:16Is it possible to see something
that, by definition, is impossible to see? -
2:17 - 2:20Well, it turns out that if we were
to zoom in at radio wavelengths, -
2:20 - 2:22we'd expect to see a ring of light
-
2:22 - 2:24caused by the gravitational
lensing of hot plasma -
2:24 - 2:26zipping around the black hole.
-
2:26 - 2:27In other words,
-
2:27 - 2:30the black hole casts a shadow
on this backdrop of bright material, -
2:30 - 2:32carving out a sphere of darkness.
-
2:32 - 2:36This bright ring reveals
the black hole's event horizon, -
2:36 - 2:38where the gravitational pull
becomes so great -
2:38 - 2:40that not even light can escape.
-
2:40 - 2:43Einstein's equations predict
the size and shape of this ring, -
2:43 - 2:46so taking a picture of it
wouldn't only be really cool, -
2:46 - 2:48it would also help to verify
that these equations hold -
2:48 - 2:51in the extreme conditions
around the black hole. -
2:51 - 2:53However, this black hole
is so far away from us, -
2:53 - 2:57that from Earth, this ring appears
incredibly small -- -
2:57 - 3:00the same size to us as an orange
on the surface of the moon. -
3:01 - 3:04That makes taking a picture of it
extremely difficult. -
3:05 - 3:06Why is that?
-
3:07 - 3:10Well, it all comes down
to a simple equation. -
3:10 - 3:12Due to a phenomenon called diffraction,
-
3:12 - 3:14there are fundamental limits
-
3:14 - 3:16to the smallest objects
that we can possibly see. -
3:17 - 3:20This governing equation says
that in order to see smaller and smaller, -
3:20 - 3:23we need to make our telescope
bigger and bigger. -
3:23 - 3:26But even with the most powerful
optical telescopes here on Earth, -
3:26 - 3:29we can't even get close
to the resolution necessary -
3:29 - 3:31to image on the surface of the moon.
-
3:31 - 3:34In fact, here I show one of the highest
resolution images ever taken -
3:34 - 3:36of the moon from Earth.
-
3:36 - 3:38It contains roughly 13,000 pixels,
-
3:38 - 3:43and yet each pixel would contain
over 1.5 million oranges. -
3:43 - 3:45So how big of a telescope do we need
-
3:45 - 3:48in order to see an orange
on the surface of the moon -
3:48 - 3:50and, by extension, our black hole?
-
3:50 - 3:53Well, it turns out
that by crunching the numbers, -
3:53 - 3:55you can easily calculate
that we would need a telescope -
3:55 - 3:57the size of the entire Earth.
-
3:57 - 3:58(Laughter)
-
3:58 - 4:00If we could build
this Earth-sized telescope, -
4:00 - 4:03we could just start to make out
that distinctive ring of light -
4:03 - 4:05indicative of the black
hole's event horizon. -
4:05 - 4:08Although this picture wouldn't contain
all the detail we see -
4:08 - 4:10in computer graphic renderings,
-
4:10 - 4:12it would allow us to safely get
our first glimpse -
4:12 - 4:14of the immediate environment
around a black hole. -
4:14 - 4:16However, as you can imagine,
-
4:16 - 4:20building a single-dish telescope
the size of the Earth is impossible. -
4:20 - 4:22But in the famous words of Mick Jagger,
-
4:22 - 4:23"You can't always get what you want,
-
4:23 - 4:26but if you try sometimes,
you just might find -
4:26 - 4:27you get what you need."
-
4:27 - 4:29And by connecting telescopes
from around the world, -
4:29 - 4:33an international collaboration
called the Event Horizon Telescope -
4:33 - 4:36is creating a computational telescope
the size of the Earth, -
4:36 - 4:38capable of resolving structure
-
4:38 - 4:40on the scale of a black
hole's event horizon. -
4:40 - 4:43This network of telescopes is scheduled
to take its very first picture -
4:43 - 4:45of a black hole next year.
-
4:45 - 4:49Each telescope in the worldwide
network works together. -
4:49 - 4:51Linked through the precise timing
of atomic clocks, -
4:51 - 4:54teams of researchers at each
of the sites freeze light -
4:54 - 4:57by collecting thousands
of terabytes of data. -
4:57 - 5:02This data is then processed in a lab
right here in Massachusetts. -
5:02 - 5:04So how does this even work?
-
5:04 - 5:07Remember if we want to see the black hole
in the center of our galaxy, -
5:07 - 5:10we need to build this impossibly large
Earth-sized telescope? -
5:10 - 5:12For just a second,
let's pretend we could build -
5:12 - 5:14a telescope the size of the Earth.
-
5:14 - 5:17This would be a little bit
like turning the Earth -
5:17 - 5:19into a giant spinning disco ball.
-
5:19 - 5:21Each individual mirror would collect light
-
5:21 - 5:23that we could then combine
together to make a picture. -
5:23 - 5:26However, now let's say
we remove most of those mirrors -
5:26 - 5:28so only a few remained.
-
5:28 - 5:31We could still try to combine
this information together, -
5:31 - 5:33but now there are a lot of holes.
-
5:33 - 5:37These remaining mirrors represent
the locations where we have telescopes. -
5:37 - 5:42This is an incredibly small number
of measurements to make a picture from. -
5:42 - 5:45But although we only collect light
at a few telescope locations, -
5:45 - 5:49as the Earth rotates, we get to see
other new measurements. -
5:49 - 5:53In other words, as the disco ball spins,
those mirrors change locations -
5:53 - 5:56and we get to observe
different parts of the image. -
5:56 - 6:00The imaging algorithms we develop
fill in the missing gaps of the disco ball -
6:00 - 6:03in order to reconstruct
the underlying black hole image. -
6:03 - 6:05If we had telescopes located
everywhere on the globe -- -
6:05 - 6:07in other words, the entire disco ball --
-
6:07 - 6:09this would be trivial.
-
6:09 - 6:12However, we only see a few samples,
and for that reason, -
6:12 - 6:14there are an infinite number
of possible images -
6:14 - 6:17that are perfectly consistent
with our telescope measurements. -
6:17 - 6:20However, not all images are created equal.
-
6:21 - 6:25Some of those images look more like
what we think of as images than others. -
6:25 - 6:29And so, my role in helping to take
the first image of a black hole -
6:29 - 6:32is to design algorithms that find
the most reasonable image -
6:32 - 6:34that also fits the telescope measurements.
-
6:35 - 6:39Just as a forensic sketch artist
uses limited descriptions -
6:39 - 6:42to piece together a picture using
their knowledge of face structure, -
6:42 - 6:46the imaging algorithms I develop
use our limited telescope data -
6:46 - 6:50to guide us to a picture that also
looks like stuff in our universe. -
6:50 - 6:54Using these algorithms,
we're able to piece together pictures -
6:54 - 6:56from this sparse, noisy data.
-
6:56 - 7:00So here I show a sample reconstruction
done using simulated data, -
7:00 - 7:02when we pretend to point our telescopes
-
7:02 - 7:05to the black hole
in the center of our galaxy. -
7:05 - 7:09Although this is just a simulation,
reconstruction such as this give us hope -
7:09 - 7:13that we'll soon be able to reliably take
the first image of a black hole -
7:13 - 7:15and from it, determine
the size of its ring. -
7:16 - 7:19Although I'd love to go on
about all the details of this algorithm, -
7:19 - 7:22luckily for you, I don't have the time.
-
7:22 - 7:24But I'd still like
to give you a brief idea -
7:24 - 7:26of how we define
what our universe looks like, -
7:26 - 7:30and how we use this to reconstruct
and verify our results. -
7:30 - 7:33Since there are an infinite number
of possible images -
7:33 - 7:35that perfectly explain
our telescope measurements, -
7:35 - 7:38we have to choose
between them in some way. -
7:38 - 7:40We do this by ranking the images
-
7:40 - 7:43based upon how likely they are
to be the black hole image, -
7:43 - 7:45and then choosing the one
that's most likely. -
7:45 - 7:47So what do I mean by this exactly?
-
7:48 - 7:50Let's say we were trying to make a model
-
7:50 - 7:53that told us how likely an image
were to appear on Facebook. -
7:53 - 7:55We'd probably want the model to say
-
7:55 - 7:58it's pretty unlikely that someone
would post this noise image on the left, -
7:58 - 8:01and pretty likely that someone
would post a selfie -
8:01 - 8:02like this one on the right.
-
8:02 - 8:04The image in the middle is blurry,
-
8:04 - 8:06so even though it's more likely
we'd see it on Facebook -
8:07 - 8:08compared to the noise image,
-
8:08 - 8:11it's probably less likely we'd see it
compared to the selfie. -
8:11 - 8:13But when it comes to images
from the black hole, -
8:13 - 8:17we're posed with a real conundrum:
we've never seen a black hole before. -
8:17 - 8:19In that case, what is a likely
black hole image, -
8:19 - 8:22and what should we assume
about the structure of black holes? -
8:22 - 8:25We could try to use images
from simulations we've done, -
8:25 - 8:27like the image of the black hole
from "Interstellar," -
8:27 - 8:30but if we did this,
it could cause some serious problems. -
8:30 - 8:34What would happen
if Einstein's theories didn't hold? -
8:34 - 8:38We'd still want to reconstruct
an accurate picture of what was going on. -
8:38 - 8:41If we bake Einstein's equations
too much into our algorithms, -
8:41 - 8:44we'll just end up seeing
what we expect to see. -
8:44 - 8:46In other words,
we want to leave the option open -
8:46 - 8:49for there being a giant elephant
at the center of our galaxy. -
8:49 - 8:50(Laughter)
-
8:50 - 8:53Different types of images have
very distinct features. -
8:53 - 8:57We can easily tell the difference
between black hole simulation images -
8:57 - 8:59and images we take
every day here on Earth. -
8:59 - 9:02We need a way to tell our algorithms
what images look like -
9:02 - 9:05without imposing one type
of image's features too much. -
9:06 - 9:08One way we can try to get around this
-
9:08 - 9:11is by imposing the features
of different kinds of images -
9:11 - 9:15and seeing how the type of image we assume
affects our reconstructions. -
9:16 - 9:19If all images' types produce
a very similar-looking image, -
9:19 - 9:21then we can start to become more confident
-
9:21 - 9:25that the image assumptions we're making
are not biasing this picture that much. -
9:26 - 9:28This is a little bit like
giving the same description -
9:29 - 9:32to three different sketch artists
from all around the world. -
9:32 - 9:34If they all produce
a very similar-looking face, -
9:34 - 9:36then we can start to become confident
-
9:36 - 9:40that they're not imposing their own
cultural biases on the drawings. -
9:40 - 9:43One way we can try to impose
different image features -
9:43 - 9:46is by using pieces of existing images.
-
9:46 - 9:48So we take a large collection of images,
-
9:48 - 9:51and we break them down
into their little image patches. -
9:51 - 9:55We then can treat each image patch
a little bit like pieces of a puzzle. -
9:55 - 10:00And we use commonly seen puzzle pieces
to piece together an image -
10:00 - 10:02that also fits our telescope measurements.
-
10:03 - 10:07Different types of images have
very distinctive sets of puzzle pieces. -
10:07 - 10:10So what happens when we take the same data
-
10:10 - 10:14but we use different sets of puzzle pieces
to reconstruct the image? -
10:14 - 10:19Let's first start with black hole
image simulation puzzle pieces. -
10:19 - 10:20OK, this looks reasonable.
-
10:20 - 10:23This looks like what we expect
a black hole to look like. -
10:23 - 10:24But did we just get it
-
10:24 - 10:27because we just fed it little pieces
of black hole simulation images? -
10:27 - 10:29Let's try another set of puzzle pieces
-
10:29 - 10:32from astronomical, non-black hole objects.
-
10:33 - 10:35OK, we get a similar-looking image.
-
10:35 - 10:37And then how about pieces
from everyday images, -
10:37 - 10:40like the images you take
with your own personal camera? -
10:41 - 10:43Great, we see the same image.
-
10:43 - 10:47When we get the same image
from all different sets of puzzle pieces, -
10:47 - 10:49then we can start to become more confident
-
10:49 - 10:51that the image assumptions we're making
-
10:51 - 10:54aren't biasing the final
image we get too much. -
10:54 - 10:57Another thing we can do is take
the same set of puzzle pieces, -
10:57 - 11:00such as the ones derived
from everyday images, -
11:00 - 11:03and use them to reconstruct
many different kinds of source images. -
11:03 - 11:05So in our simulations,
-
11:05 - 11:08we pretend a black hole looks like
astronomical non-black hole objects, -
11:08 - 11:12as well as everyday images like
the elephant in the center of our galaxy. -
11:12 - 11:15When the results of our algorithms
on the bottom look very similar -
11:15 - 11:18to the simulation's truth image on top,
-
11:18 - 11:21then we can start to become
more confident in our algorithms. -
11:21 - 11:23And I really want to emphasize here
-
11:23 - 11:25that all of these pictures were created
-
11:25 - 11:28by piecing together little pieces
of everyday photographs, -
11:28 - 11:30like you'd take with your own
personal camera. -
11:30 - 11:33So an image of a black hole
we've never seen before -
11:33 - 11:37may eventually be created by piecing
together pictures we see all the time -
11:37 - 11:40of people, buildings,
trees, cats and dogs. -
11:40 - 11:43Imaging ideas like this
will make it possible for us -
11:43 - 11:45to take our very first pictures
of a black hole, -
11:45 - 11:48and hopefully, verify
those famous theories -
11:48 - 11:50on which scientists rely on a daily basis.
-
11:50 - 11:53But of course, getting
imaging ideas like this working -
11:53 - 11:56would never have been possible
without the amazing team of researchers -
11:56 - 11:58that I have the privilege to work with.
-
11:58 - 11:59It still amazes me
-
11:59 - 12:03that although I began this project
with no background in astrophysics, -
12:03 - 12:05what we have achieved
through this unique collaboration -
12:05 - 12:08could result in the very first
images of a black hole. -
12:08 - 12:11But big projects like
the Event Horizon Telescope -
12:11 - 12:14are successful due to all
the interdisciplinary expertise -
12:14 - 12:15different people bring to the table.
-
12:15 - 12:17We're a melting pot of astronomers,
-
12:17 - 12:19physicists, mathematicians and engineers.
-
12:19 - 12:22This is what will make it soon possible
-
12:22 - 12:25to achieve something
once thought impossible. -
12:25 - 12:27I'd like to encourage all of you to go out
-
12:27 - 12:29and help push the boundaries of science,
-
12:29 - 12:33even if it may at first seem
as mysterious to you as a black hole. -
12:33 - 12:34Thank you.
-
12:34 - 12:37(Applause)
- Title:
- How to take a picture of a black hole
- Speaker:
- Katie Bouman
- Description:
-
At the heart of the Milky Way, there's a supermassive black hole that feeds off a spinning disk of hot gas, sucking up anything that ventures too close -- even light. We can't see it, but its event horizon casts a shadow, and an image of that shadow could help answer some important questions about the universe. Scientists used to think that making such an image would require a telescope the size of Earth -- until Katie Bouman and a team of astronomers came up with a clever alternative. Learn more about how we can see in the ultimate dark.
- Video Language:
- English
- Team:
- closed TED
- Project:
- TEDTalks
- Duration:
- 12:51
Brian Greene edited English subtitles for How to take a picture of a black hole | ||
Brian Greene edited English subtitles for How to take a picture of a black hole | ||
Brian Greene edited English subtitles for How to take a picture of a black hole | ||
Camille Martínez accepted English subtitles for How to take a picture of a black hole | ||
Camille Martínez edited English subtitles for How to take a picture of a black hole | ||
Camille Martínez edited English subtitles for How to take a picture of a black hole | ||
Leslie Gauthier edited English subtitles for How to take a picture of a black hole | ||
Leslie Gauthier edited English subtitles for How to take a picture of a black hole |