so in the movie interstellar we get an
up-close look at a supermassive black
hole set against the backdrop of bright
gas the black hole's massive
gravitational pull bends light into a
ring however this isn't a real
photograph but a computer graphic
rendering an artistic interpretation of
what a black hole might look like 100
years ago Albert Einstein first
published his theory of general
relativity in the years since then
scientists have provided a lot of
evidence in support of it but one thing
predicted from this theory black holes
still have not been directly observed
although we have some ideas to what a
black hole might look like we've never
actually taken a picture of one before
however you might be surprised to note
that it may soon change we may be seeing
our first picture of a black hole in the
next couple years getting this first
picture will come down to an
international team of scientists an
earth-sized telescope and an algorithm
that puts together the final picture
although I won't be able to show you a
real picture of a black hole today I'd
like to give you a brief glimpse into
the effort involved in getting that
first picture so my name is Katie
bellman and I'm a PhD student at MIT I
do research in a computer science lab
that works on making computer
see-through images and video but
although I'm not an astronomer today I'd
like to show you how I've been able to
contribute to this exciting project so
if you go out past the bright city
lights night you may just be lucky
enough to see a stunning view of the
Milky Way galaxy and if we could zoom
past millions of stars 26,000 light
years towards the heart of the
spiralling Milky Way we'd eventually
reach a cluster of stars right at the
center peering past all the galactic
dust with infrared telescopes
astronomers have watched these stars for
over 16 years but it is what they don't
see that is the most spectacular these
stars seem to orbit an invisible object
by tracking the paths of these stars
astronomers have concluded that the only
thing small and heavy enough to cause
this motion is
supermassive black hole an object so
dense that it sucks up anything that
ventures too close even like but what
happens if we were to zooming even
further is it possible to see something
that by definition is impossible to see
well it turns out that if you were to
zoom in at radio wavelengths we expect
to see a ring of light caused by the
gravitational lensing of hot plasma
zipping around the black hole
in other words the black hole casts a
shadow on this backdrop of bright
material carving out a sphere of
darkness this bright ring reveals the
black hole's event horizon where the
gravitational pull becomes so great then
not even light can escape Einstein's
equations predict the size and shape of
this ring so taking a picture of it
wouldn't only be really cool it also
helped to verify that these equations
hold in the extreme conditions around
the black hole
however this black hole is so far away
from us so from Earth this ring appears
incredibly small the same size to us as
an orange on the surface of the Moon
that makes taking a picture of it
extremely difficult why is that well it
all comes down to a simple equation due
to a phenomenon called the fraction
there are fundamental limits the
smallest objects that we can possibly
see this governing equation says Ben in
order to see smaller and smaller we need
to make our telescope bigger and bigger
but even with the most powerful optical
telescopes here on earth we can't even
get close to the resolution necessary to
image on the surface of the Moon in fact
here I show one of the highest
resolution images ever taken of the moon
from Earth it contains roughly 13,000
pixels and yet each pixel will contain
over 1.5 million oranges so how big of a
telescope do we need in order to see
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
at up the size of the entire Earth and
if it could build this earth sized
telescope we could just start to make
out that distinctive ring of light
indicative of the black hole's event
horizon although this picture wouldn't
contain all the detail that we get to
see in computer graphic rendering it
would allow us to safely get our first
glimpse of the immediate environment
around a black hole
however as you can imagine building a
single dish telescope the size of the
earth is impossible but in the famous
words of Mick Jagger you can't always
get what you want but if you try
sometimes you might just find that you
get what you need and by connecting
telescopes from around the world an
international collaboration called the
event horizon telescope is creating a
computational telescope the size of the
earth capable of resolving structure on
the scale the black hole's event horizon
this network of telescopes is scheduled
to take us very first picture of a black
hole just next year each telescope in
the worldwide network works together
linked through the precise timing of
atomic clocks teams of researchers at
each of the sites freeze light by
collecting thousands of terabytes of
data this data is then processed in a
lab right here in Massachusetts so how
does this even work well remember if we
want to see the black hole in the center
of our galaxy we need to build this
impossibly large
earth sized telescope so for just a
second let's pretend we could build this
health scope the size of the earth this
would be a little bit like turning the
earth into a giant spinning disco ball
each individual mirror would collect
light that we could then combine
together to make a picture however now
let's say we removed most those mirrors
so only a few remained we could still
try to combine this information together
but now there are a lot of holes these
remaining mirrors represent the
locations where we have telescopes this
is an incredibly small number of
measurements to make a picture from but
although we only collect light at a few
telescope locations as the Earth rotates
we get to see other new measurements in
other words as the disco ball spins
those mirrors change locations and we
get to observe different parts of the
image the imaging algorithms we develop
fill in the missing gaps of the disco
ball in order to reconstruct the
underlying black hole image as we had
telescopes located everywhere on the
globe in other words the entire disco
ball this will be trivial however we
only see a few samples and for that
reason there an infinite number of
possible images that are perfectly
consistent with our telescope
measurements however not all images are
created equal some of those images look
more like what we think of as images
than others and so my role in helping
take the first image of a black hole is
to design algorithms that find the most
reasonable image that also fits the
telescope measurements just as a
forensic sketch artist uses limited
descriptions to piece together a picture
using his knowledge of face structure
the imaging algorithms I developed use
our limited telescope data to guide us
to a picture that it also looks like
stuff in our universe using these
algorithms we're able to pick piece
together pictures from the sparse noisy
data so here I show a sample
reconstruction done using simulated data
when we pretend to point our telescopes
to the black hole in the center of our
galaxy although this is just a
simulation reconstruction such as this
give us hope that we'll soon be able to
reliably take the first image of a black
hole and from it determine the size of
its ring although I'd love to go on
about all the details of this algorithm
luckily for you I don't have the time
but I still like to give you a brief
idea of how we define what our universe
looks like and how we do this how we use
this to reconstruct and verify our
results since there an infinite number
of possible images that perfectly
explain our telescope measurements we
have to choose between them in some way
we do this by ranking the images based
upon how likely they are to be the black
hole image and then choosing the one
that's most likely so what do I mean by
this exactly let's say we were trying to
make a model that told us how likely an
image were to appear on Facebook we
probably want the model to say that it's
pretty unlikely someone would post this
noise image on the left and it's 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 that we've seen on Facebook
compared to the noise image it's
probably less likely we see it compared
to the selfie but when it comes to
images from the black hole
we're posted the real conundrum we've
never seen a black hole before in that
case what is a likely black hole image
and what should be assumed 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 theories didn't hold
we still want to reconstruct an accurate
picture of what was going on if we baked
Einstein's equations too much into our
we'll just end up seeing what we expect
to see in other words we want to leave
the option open so there being a giant
elephant at the center of our galaxy
different types of images have very
distinct features we can easily tell the
difference between black hole simulation
images and images we take every day here
on earth we need a way to tell our
algorithms what images look like without
imposing one type of images features too
much one way we can try to get around
this is by imposing the features of
different kinds of images and seeing how
the type of image we assume affects our
reconstructions if all images types
produce a very similar looking image
then we can start to become more
confident that the image assumptions
we're making are not biasing this
picture that that much 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 one way we can try to
impose different imaging features is by
using pieces of existing images so we
take a large collection of images and we
break them down into their little image
patches we then can treat each image
patch a little bit like pieces of a
puzzle and we use commonly seen puzzle
pieces to piece together an image that
also fits our telescope measurements
different types of images have very
distinctive sets of puzzle pieces so
what happens when we take the same data
but we use different sets of puzzle
pieces to reconstruct the image so let's
first start with black holes black hole
image simulation puzzle pieces okay this
looks reasonable this looks like what we
expect a black hole to look like but did
we just get it because we fed it little
pieces of black hole simulation images
let's try another set of puzzle pieces
from astronomical non black hole objects
okay we get a similar looking image and
then how about pieces from everyday
images like the images you take with
your own personal camera great we see
the same image when we get the same
image from all different sets of puzzle
pieces then we can start to become more
confident that the image assumptions
we're making aren't biasing the final
image we
too much another thing we can do is take
the same set of puzzle pieces such as
the ones derive from everyday images and
use it to reconstruct many different
kinds of source images so in our
simulations we pretend the black hole
looks like astronomical non black hole
objects as well as everyday images like
the elephant in the centre of our galaxy
when the results of our algorithms on
the bottom look very similar to the
simulations truth image on top then we
can start to become more confident in
our algorithms and I just really want to
emphasize here that all of these
pictures were created by piecing
together little pieces of everyday
photographs like you take with your own
personal camera so an image of a black
hole we've never seen before may
eventually be created by piecing
together pictures that we see all the
time of people buildings trees cats and
dogs imaging ideas like this will make
it possible for us to take our very
first pictures of a black hole and
hopefully verify those famous theories
for which scientists rely on a daily
basis 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 what we have
achieved is this unique collaboration
could result in the very first images of
a black hole but big projects like the
event horizon telescope are successful
due to all the interdisciplinary
expertise different people bring to the
table we're a melting pot of astronomers
physicists mathematicians and engineers
and this was what this is what will make
it to impossible to achieve something
once thought impossible and so 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
you as a black hole thank you
[Applause]