Hello, I'm Dallas Campbell. And in this series of videos, we're going to be showing you how
to become a citizen scientist, how you can take
part in real scientific experiments and help researchers make genuine discoveries about
the world and the universe beyond. Well, today, I have come to a rather damp
breakers yard in southeast London to try and understand how dented cars can tell us all
about warping in space and time. To help me, I'm
joined by Andrew Davies from the Open University. Why on Earth have you brought me here?
So, for my PhD project, I've been looking at warps. And warps are caused by a mass in
space-time. We're looking for arcs, which are warped distant galaxies caused by the
mass of a full-grown galaxy warping or distorting the space-time to give rise to these images.
So, what's the link between that and say a dent in a car door like this one?
So, car companies may use similar technology-- artificial intelligence-- to look for these
warps or dents in the car body to try inferring
the damage on the car based on those images and the
warps they find. OK, so the AI will look at a car panel go,
oh look, there's a dent in it. But I can look around
and use my eyes. I mean, I can see there's a great big dent in this car, for example.
Could I look at your pictures from space and see warping
of space-time? Yes, you can. So, we have simulated images
for the Euclid telescope, which you can actually see with your eyes these arcs or distortions
or warps in space-time. What's better at it, an AI machines or humans?
This is exactly what the citizen science project is trying to learn. We have AI technology,
which has already looked at these images, and we have scores for them. Unfortunately,
we can't-- we haven't got scores for humans.
Well, our citizen scientist, Alice, [INAUDIBLE]. She's looking at some of your images.
Right now, I'm looking at the gravitational lens, which I found on Euclid-- Challenge
the Machines. In the middle is a bright yellow
core, a bit of an oval. Around that is a lovely ghostly
bluish-grey ring. Now the reason that's formed is we've got
a galaxy relatively close to us, like this, and behind
it, we've got another galaxy. The light from this other galaxy behind us, it can't go through
that yellow one in front. It's blocked.
However, light can go sideways. It goes out in all directions. So, it went out like this,
then the gravity from this one pulled it in again,
so it went like this. Now imagine it happening all
around that and that's what gives us this beautiful ring. It looks fantastic.
Though I'm trying to find anything that looks like this. It might not be the whole ring.
If the galaxy wasn't completely lined up, then you'll
just see a little arc or a little patch. You get to
know after a while which is a lens, and which isn't.
Once you've got this data, once you understand it, what's the point of it? Why do you need
to understand this in the first place?
Well, the point of this is to learn why the machines are better and how we can improve
them for future missions.
So, is this more of a project about machine learning rather than astronomy?
Yes. Yes. So, we want the technology to be able to scan through millions and billions
of images so that for future space missions,
when we have all this data, we don't have to look
through them painfully. So this whole project is about seeing what
is best, computers versus humans. So, if you were
a betting man and you weren't running this project, where would you put your money?
My money would be on the machines— Really? --over humans.
Have you, have you met Alice? She's good. She's working very hard. I'm going to put
a tenner on Alice.
- Hi, I'm Dallas Campbell and in this series of videos, we're going to be showing you how
to become a citizen scientist, taking part in
real scientific experiments and helping researchers make discoveries about the world and the universe
beyond. And we're very lucky today because we going to be looking at how to detect
cosmic particles with your mobile phone. I'm very lucky to be here with Dr Jo Jarvis from
The Open University. And Dr Alex? Maybe a doctor-
- I meanDALLAS CAMPBELL: One day - Maybe, maybe.
DALLAS CAMPBELL: University of life, he's going to be our citizen scientist. Well, first
of all, what is a cosmic ray? It sounds very esoteric;
it sounds very science-fiction. What are we talking about?
- They are a bit. [LAUGHS]
Cosmic rays are really high energy particles that are raining down on our planet from space
all the time. They're passing through us right now.
- OK. - Don't worry.
- They're going through my- - Yep, Yep don't worry they're not doing any
harm at all. - I'm guessing they are not very big.
- No, they're not. No, they're much, much smaller than sort of electrons and things
that you might be more familiar with, but they carry
huge amounts of energy with them. - So even though these particles are passing
through me and tables and chairs and planets how do we detect them because I presume, they're
going through the phone itself. - They all are going through the phone itself
yes absolutely. But the CCD chip that is in there
that you're actually taking your photo on- - So, this is from the camera bit-
- It's the camera. Yeah absolutely, that is that's really quite dense that's a very solid
piece of material.
DALLAS CAMPBELL: Yeah. - So, as the particles travel through that
they actually leave a little bit of energy behind and we
see that as an image. As one maybe two pixels lit up.
DALLAS CAMPBELL: So, we're not seeing the particle itself, we're just seeing it's sort
of trail- - Exactly.
- If you like. How is a mobile phone going to pick that up? How are we going to detect
these things?
- Well, first what you need to do is pop an app on your phone, just like any other app.
And it's called CREDO detector.
- Yeah. - And it will be using the camera on the back
of your phone which you need to just cover up.
What it is doing, I'll show you some statistics, there we go. So you can see the frames busy
counting up. So that is constantly taking pictures.
- So, this is a visual thing, this is a visual that's taking actual snapshots.
- Absolutely. - Alex, here is the phone. I want you to do
a little bit of citizen science for me and see if you
can detect a cosmic ray. - I shall start the detection. Go!
DALLAS CAMPBELL: How often are they hitting because that camera lens is very, very
small. - It is very small, yeah absolutely.
- I guess the cosmic particle is also- - It's also extremely small. Yeah, so if you
were to work out you know the statistics of you
know a particle hitting your camera phone- - Yeah
- Then it's really quite small. Of course, there are millions and millions of phones
like this scattered across the planet.
- And this is why it's a good citizen science project because everybody has a phone. So
everyone is carrying a particle detector- - Absolutely, absolutely. We-- with the help
of citizen scientists we have got a detector the
size of the planet. - Dr Alex, what have you detected? Have you
come up with something? - Oh yes, that's quite a good two there.
- OK, so that looks to the untrained eye, that looks like two splotches.
- Yep, we've got, we've actually got two detections there.
DALLAS CAMPBELL: So, there's a two particlesJO JARVIS: Come in together
DALLAS CAMPBELL: That have hit. And presumably, all this data is going to be passed on to
someone soJO JARVIS: Yeah absolutely DALLAS CAMPBELL: Two particles.
JO JARVIS: Yeah. - The question is though why do we care? I
mean why collect all this data for what purpose. - They carry a huge amount of information
for us. So, from a sort of scientist perspective, we
can gather information about the Big Bang, where the universe and us originally came
from. They can potentially help to answer some of
the fundamental questions such as dark matter that you might have heard of and what it is.
But also, much, much closer to home we're already aware of the fact we have to be a
little bit cautious about what the sun is up to in
terms of exposing astronauts to danger and affecting communication satellites things
like that. We haven't really looked at the effect of
cosmic rays. - Apart from now, Alex, I'm going to give
you back this. Continue with your science. Jo, thank
you very much indeed for that. (WHISPERS) There's also the space invaders app on there
in case you want to do that.
Hello, I'm Dallas Campbell. And in this series of videos, we're going to be showing you how
to become a citizen scientist, taking part in
real scientific experiments, helping researchers make
discoveries about the world and the universe beyond. And today we're going to be looking
at how the human ability to be able to recognize
and identify weird anomalies is going to help us
find binary stars. And I'm very lucky to have two of Britain's
finest scientific minds here. Professor Andrew Norton and Yo-Yo the Clown. Do you know much
about binary stars, Yo-Yo? Is that your special, oh, star, there's a star. Single
star. OK, I have a star. Your star has vanished. And
my, my star has become two stars! Andrew, is that a binary star?
Exactly so. Thank you. We're used to seeing a single star in the sky, the sun.
Yes, yeah. But at night-time, many of the stars we see
are actually two or more stars orbiting around each other. They're born at the same time.
Like in Star Wars. Just like in Star Wars. And two stars may
be going around each other. Now, to our human eyes, they're too close together. We can't
see that it's two. But the light that we detect from
these stars changes as one passes in front of the other.
OK, so why are we here on London Bridge? OK.
With Yo-Yo, the very wonderful clown and his sponge. But what's clowning got to do with
binary stars? So, when we look at the light from these stars,
we can train computers to spot these binary stars, if they're behaving normally.
OK. And we can pick those out. But if one of them
is behaving strangely, the computer wouldn't say, that's a strange binary star. It would
just say, that's something peculiar that we can't
understand. Same way we could train a computer program to pick out people. It might see
Yo-Yo the Clown and say either, well, that's just an ordinary person or it's not a person
at all. Whereas we, with our human eyes.
Oh, I see, yes. Say that's just an unusual human being.
So, computers are good, but they don't make any judgments.
Exactly so. Whereas, we can look at a clown and go, there's
a man wearing funny shoes. What is it you want to do with a citizen science project?
What's the kind of, what's the plan? So, we want people to identify these binary
stars. So actually, just sitting back down and looking
visually with our eyes. Exactly. We have some patterns of how their
brightness varies. OK.
And people can step through, look at hundreds of these and find the interesting ones.
But luckily enough, we have Alice, our citizen scientist, who are doing just that. She's
actually looking at some photos of binary stars.
We're looking at a sort of graph. It's a black background, it's got wonderful white speckles
leveraged in a sort of V shaped pattern, as if someone sprinkled flour over it. In the
middle of all these white speckles is a red line. What
we're hoping, is that the white speckles and the
red line will show us quite a regular pulsating series of V shapes.
This one is different from the other ones. This is called an eclipsing binary. This is
two stars that are so close to each other, they might
even be exchanging material. They're going behind each other from our point of view,
very regularly. So of course, sometimes we'll see
the light from both, and sometimes we'll see the light just from one of them.
So, she's looking here at patterns of how the brightness of stars vary with time.
OK. And she can pick out the ones that are binary
stars. But what she'll also be able to do, is pick
out the unusual binary stars. They may have spots on one side, like Yo-Yo's tie. Or they've
got a very bright patch on the other side, like his nose. And picking those things out
can help us find the unusual stars. And the human eye
can pick those out better than a computer can.
Is this project, is it an exercise in understanding more about binary stars? Or is it an exercise
at trying to work out whether AI is better than the human brain or vice versa?
So, in the first instance, this will help us find the binary stars, because they're
the only way we can directly measure the mass or the size
of a star. And so, understand how they're born or
evolve or die. And so, we know how our sun then works. But moving forward, this will
help us train computers better to recognize these
strange things in the future. I got to say, I don't think you're a strange
thing at all. I think he's perfectly normal. I would look
at, I would look at you and go, nothing to see here.
[LAUGHTER] [MUSIC PLAYING]
Hello, I'm Dallas Campbell. And in this series of videos, we're going to be showing you how
to become a citizen scientist, taking part in
real scientific experiments and helping researchers make discoveries about the world and the universe
beyond. And today, I'm going to show you how the science of litter picking can actually
help you weed out contaminants when we're looking for precious data about gamma rays.
And to help me, I'm going to talk to Professor Lucy Fortson in America. Hi, Lucy, thanks
for joining us. Just first of all, what do you mean
when you talk about contaminants? Cosmic rays, when they hit the top of the
atmosphere, much like gamma rays, generate daughter particles. They go through the atmosphere
generating up to billions of separate particles in what we call an air shower.
OK. And in that process, they also create muons.
And they can actually create these rings out of
something called Cherenkov light. So, the ring's a particle, the muon comes through,
creating a ring. The ring gets picked up in our camera.
Aha. So, we call those, they're contaminating your camera.
They are contaminating our camera. Well, their good purpose is, we know exactly how much
light should be in one of those rings. And so, we can actually use them to calibrate
our cameras.
OK, so let me ask you about a litter picking. So, I'm outside picking up litter from the
hedgerows. What has that got to do with contaminants and gamma rays?
If you were to be out in a hedgerow say, collecting or recycling plastic bottles, then if you
were to be looking for these plastic bottles, but
let's say there's a bunch of crisp packets nearby or
something like that, you might get confused. You might not actually be able to tell the
difference on first glance. For computers, which we would like to be able to process
all the data, it can actually be quite difficult to
tell the difference between one of the snippets or
edges of a ring made by the muons versus one of the tracks made by the gamma ray.
Well, we've got our citizen scientist, Alice, who is looking at some of these images now
I've got a grid of six by six dark blue circles. And in these dark blue circles, are lovely
little splashes of every color of the rainbow. Some
of them slightly arc-shaped. A little crescent, a
little arc. Sometimes even a little circle. And the rest are just sort of random cloudy
bits. So here you can see almost a complete circle,
but because it's so many different colors, that's
going to be really tough for a machine to assess.
But for us humans, it's pretty easy. The ones that are actual circles are muons, the heavy
cousin of the electron. and It's fascinating to think of them flying across the universe
and hitting our detectors, and then appearing
on my screen is this lovely little arc. So, you're going to generate all this data,
thanks to citizen scientists. What's the point? Why is
studying gamma rays interesting? We want two things out of this. The first
is, we want to find a lot more rings. And those rings
we can use to actually calibrate the instrument. But preferably, we would really like to tell
the difference between the little bits of ring
that masquerade as gamma rays, so we can clean those out of the system and we can get a much
better set of gamma rays that point back to interesting astrophysical phenomena, like
supernova that are exploding or the jets of material
that are spewing out of active galaxies, that sort of thing. Stuff that we like to study.
Got it. Thank you so much. I'm going to go outside and do a bit more litter picking now.
There's lots of muons out there that need tidying up. OK.
Bye bye have fun. Nice to meet you, bye, bye. There are loads
more citizen science projects you can take part
in, from penguins spotting in Antarctica to helping rescue teams target age and resources
during natural disasters. Find out more on the citizen science website.
Get more from the Open University
Check out the links on screen now.