Thank you! I'm so sorry! This is live, as
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this is a live talk and I will be talking about
CERN and particle physics and the ATLAS detector.
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Okay, oh, so my video is also covering up... this is something I should have checked.
I'm gonna move me over here.
Okay. So I am a particle physicist. I work
on the ATLAS experiment
which is based at the laboratory CERN.
So where is CERN and what is CERN?
Here is our planet and we're going to zoom in to Europe
and specifically to the border between
Switzerland and France.
It's near Geneva.
And so here you can see an aerial view of CERN.
This is the Large Hadron Collider.
It is a 27 kilometre long
tunnel with an accelerator inside where we
accelerate protons to almost the speed of
light. And we collide them at four points
around the ring. So we have the CMS detector,
LHCb, ATLAS, which is the one that I work
on. And ALICE, which is another detector.
And you can see here in the in the bottom
right for me, I think it should be bottom
right for you as well. So this is actually
Geneva airport and this is the lake in Geneva
so you can get a sense of the scale. It is
a huge, huge particle accelerator.
And so as I said, we accelerate protons around
this accelerator, and we collide them
in the centre of the detectors. So we have,
yeah, so you can see that when the protons
come together, they the energy, so we use
E=mc squared, this is the famous Einstein
equation. And to say that energy and matter
are equivalent with a factor of the speed
of light squared. And so from the matter, the
stuff of the protons, we can collide them
together, turn this into energy, this energy
then turns into new particles, such as the
Higgs boson, for example. And these new particles
don't last for very long. We say that
they're not stable it means because they're
heavy particles, and so they change
into lighter particles. And these have travelled
through our detector in the sort of firework
shape, and then we measure them in different
parts of our detector. Now, this is the Standard
Model of particle physics. This is our recipe
book. And so we have quarks which are shown
here in dark blue, we have leptons, which
are shown in this sort of medium blue at the
bottom. And these are all stuff, these are
the things that make up
matter.
And then in the centre, we have bosons, and
these are the force particles. So for example,
each are associated with the type of force.
So the photon is one you might be familiar with
and this is associated with electromagnetism.
And we have the strong force where the gluon
is the particle, the boson that propagates
this force. Then we have the weak and the W
and the Z bosons which are associated with
the weak nuclear force. Now the weak nuclear
force is really important, it's how our
sun is powered. So it's really important for
life on this planet. The electromagnetism,
one you're probably relatively familiar with
a strong force is actually what binds particles
together. So in a proton, we have these gluons,
which bind the protons together. And then we
also have the Higgs boson, which I'll talk
about a bit later. Okay, so here's a proton.
And the proton is made up of quarks so that's
what I was talking about here. So the lightest
quarks, the up and the down. So we have three
of them, which make up a proton, and they're
held together by gluons and then also as we
increase the energy that we give the proton, we also have some other quarks
that will pop in and out of existence in pairs
So this is quite an
important thing to remember for the Large
Hadron Collider because a proton is a hadron and it's that we have to take into account
when we collide these protons together in
our detectors [that] we don't know which one of
these is actually doing the colliding. So
even though we can give protons a certain
amount of energy, we don't necessarily get
to pick which quark or gluon collides and
therefore which energy they have. That's something
we have to take into consideration when we're
doing our measurements. Now, this is the ATLAS
detector, it is the detector that I work on.
So here for scale, you have two people and
then I also added a T Rex, because I thought
the people were too small but you can see that
it's 44 metres long, it's 25 metres tall.
And you don't need to worry about all these
labels at the bottom it's just to show you that
we have this kind of construction of the detector
where the collisions happen right here in
the very centre and then we surround it by
different segments of detector that have a
different job in measuring these particles
that come out as I described.
Now I'm just gonna check...
I'm gonna pause my share... I stopped
sharing just so that I can check the chat...
Okay, I don't see any complaints. I think
I can still be heard. Great! So now I want to
go back... oh and my balloon is having trouble... okay.
So let's go back to the presentation.
Okay, wonderful. So we're back here. So yeah,
this is the ATLAS detector. I've worked on
this detector for over 10 years now. And it
is a really complicated detector.
It's huge, as you can see. And so there are thousands
of people that have worked on this and contributed
to it. So here's a photograph I took when
I was underground one time. And so these detectors
are actually about 100 metres underground.
And here you can see... Oh, no... you can't...
err...this one...
Okay, so here now you can see this blue pipe.
So this is where the beam pipe is inside.
And then here we have different... So this is
actually the muon wheel of the ATLAS detector.
So hopefully with this sort of fisheye photograph,
you get a sense of just how huge and complicated
this machine is. And if you if you go on to
the ATLAS social media, just to give a little
bit of a plug, we have a 360 degree tour that
one of my colleagues did of this area. So
you can see a lot more from a lot more different
angles, the detector. Okay. So as I said before,
there are a lot of people working in this
collaboration. So this is just the ATLAS Collaboration,
which is one experiment on the Large Hadron
Collider. And we have over 5500 members of
103 different nationalities and this was in
November 2018, so the numbers could have changed
slightly, but there are thousands of people
who are working on this. No one person can
do everything. So it's really important
that we collaborate with people from different
countries and work together.
Okay, so I showed you all of these different
parts of the detector. But let's... I want to
give you now an idea of what what they do,
why do we have these different components?
So, here is the beam pipe. So from that we're
looking into the beam. The first segment we
have are the tracking part
of the detector.
So particles that have charge, such as an
electron, or a proton
or a photon. And because we don't really have
protons going through this, but as they as
they come from the centre of the collision,
then they will travel through this part of the
detector. So I actually can turn this on, and you
can see. So here we have an electron and it travels
through the tracking part of the detector and
as it travels through, it knocks other electrons
out within the detectors, pixel detector,
for example, and we actually measure these
electrons and we measure the charge as they go through.
Then we also have this segment of the detector.
So we have the electromagnetic calorimeter
and the hadronic calorimeter.
And these two are designed to measure energy.
So the particles when they travel through,
they deposit their energy in the detector
and from that we can measure it. So there's
two because we have one that measures the electromagnetic deposits and one that measures hadronic.
So, oh, I didn't want to do that.
Start that again...
Okay, so you can see now that the photon
has gone through and it's not charged,
as I accidentally said earlier, but it does leave energy in the electromagnetic
calorimeter. And then, oh we do have protons - sorry.
Yeah, so we have protons that go through we
have neutrons that go through, of course, these travel through our detector and so the proton
which has charge will leave its deposit along
the way and it will deposit most of its energy
in the hadronic calorimeter, whereas,
the neutron which is not charged, will travel
through the detector and deposit it's energy 
in the hadronic calorimeter. So, you can think of this like
a fingerprint; each different particle
leaves a different kind of trace through our
detector. So, some of them will
be charged and leave their deposits in
one of the calorimeters, some of them won't be.
And then we have the muons which travel
all the way through our detector. They are charged
but they don't leave all of their energy in the
calorimeters, so we have a detector right
on the outside, which just measures muons.
And then from the Standard Model, that recipe
book that I showed you earlier, the only particles
that are left after we've measured all these
are the neutrinos, and these don't leave any
trace in our detector, we can't measure them.
They're extremely light, they interact very
rarely. So how can we actually measure a neutrino
in our detector is that we look for missing
transverse momentum.
So we know that momentum should be conserved
in our detector. So we can look at where there's
a loss of momentum in one direction. And then
to balance it out. We say that there should
have been something in the other direction.
And so we can infer that that was a neutrino.
Now if we are able to find, which I'm going
to mention a bit later, something like dark
matter. And it is a particle that also doesn't
interact with our detector, then this would
also leave missing momentum. So it's one way
that we can look for particles that we aren't
usually seeing in our detector. we infer that
they were there. But yeah, so we have all
of these different particles that go through,
and we measure them like a fingerprint. And
so this is a picture I just want to show you.
So I did my PhD working on the pixel detector,
which was that very first layer that we saw
in the previous image. And so I designed and
tested prototypes for upgrading this part
of the detector. And the pixel detector [that] I worked
on in my PhD is now in the ATLAS detector.
So that's really nice that something I worked
on directly is measuring in the ATLAS detector.
But again, there were huge teams of us working
on this because it's definitely a group effort.
So we've got all of these particles that have been
measured in our detector, the collisions in
the Large Hadron Collider happen every 25 nano-seconds, which is extremely quickly. So we
get about 600 million collisions every second.
And that number changes a bit depending on how
closely we packed the protons together. But
it's a lot of collisions. So what happens?
We get these collisions, we measure the tracks
through our detector, and then we read them out,
but the new particles that are created in these collisions aren't always necessarily interesting.
There are some that happen so
frequently that we don't need to measure them anymore.
So what we do is we have very fast
electronics that have been designed by my
colleagues in the ATLAS Collaboration, and
these electronics are programmed to make decisions
about which of the events, we call
them, which of these fingerprints of all the
measurements that we've taken are interesting
what could have new physics, what could have
have a Higgs boson? And, and so we only keep
the ones that are interesting.
And then we send it on to processors that further
take a look at the information and throw away
more data. So we are recording so much information
in these collisions that we can't possibly
store it all. And so we really have to throw
away a lot of this data. as we're going along,
we have to very, very quickly make decisions:
What is interesting? What's important to keep?
and then send it to these data centres, where
it can be stored, where it can be sent on to
other data centres around the world,
for particle physicists who are based not just at CERN, but around the world at universities
everywhere, to then study these events and
to see if there's something interesting in them.
So I'm just going to skip ahead a bit with this video,
because I want to show you what I've just told you.
So, from Geneva from what we
call to Tier 0, we then send this information around
to the world. And really all over the planet,
people can analyse this data, which is also
quite interesting thing for the current situation
we find ourselves in, because quite used to
as particle physicists being distributed across
the planet and working from different places.
So actually, I am able to do my physics analysis
work from my laptop in my, currently, my parents
house, because I can access this data from
from anywhere I have an internet connection.
So it's really great that it's
distributed in this way that we can work
from anywhere. Okay, so if you want to find
a new particle, can you just go to your favourite
search engine and search for brand new particles?
So, sadly, it doesn't work like that.
We are trying to understand the building blocks
of the Universe and what everything that
we can see around us is made of, how it interacts
with each other. So what are... Yes, so it's
a very complicated thing to be doing. So what are the some of the big questions
in particle physics right now? One of the
big questions was the Higgs boson. So this
was theorised by six theorists, one of which
was Peter Higgs, about what gets particles mass.
So I'll talk a bit more about that in
a moment. We also want to know what dark matter is.
So about 5% of the Universe is visible
matter. It's that stuff I was talking about
earlier. It's you, it's me, it's the trees,
it's the planets, the moon, this is all
visible matter. This is all stuff. So we also
want to know what dark matter is. So dark
matter has been measured in our Universe,
we know it's there. We just don't know what
it is. And so the main reason we know it's
there is from the rotation of galaxies in,
in space, they rotate faster at the edges
than we expect them to. So this tells us that
there's more mass in the edges of galaxies
than we see through other means.
We can also see the effect of dark matter
through things like gravitational lensing.
So this is the warping of space-time as light
travels along it, and you get these sort of
optical distortion images when you're looking
at space, that tells us that there's a lot
of stuff there, but we don't measure it through its interaction with light, for example.
Yeah, and then also we have 68%, around, of
the Universe is dark energy. But that's a
whole other factor with.
We're definitely not there yet.
So one of the suggestions, or one of the theories,
that we have in particle physics of what dark
matter could be, is this theory called supersymmetry.
So all of those particles I showed you at
the beginning from the Standard Model,
it's hypothesised that they have a partner
in the supersymmetric theory. And it could
be, if this is true, that one of these particles
the lightest, perhaps, is a dark matter particle.
So finding any of these particles would give
us the indication that there is one that
is dark matter, or that there is new physics
that we're looking for. But unfortunately,
if it is true, it's very elusive, because
we've been looking for it for quite a long
time. And we have no hints that it's there
yet. So it's one of the theories that we're
looking at by them. So far, no, no evidence.
There's also the matter-antimatter asymmetry.
So we're really glad this exists, because
otherwise we wouldn't. But this is the observation
there is more matter than antimatter in the
Universe, and we want to know, where did it
all go? Why did this happen? So we know that
antimatter exists. So for example, this here
is the first photograph of antimatter. It's a
positron, which is an anti-electron. And what
we have is an 'electron' coming through this
apparatus. This is a lead plate and as... so
it's actually coming... yeah, it's coming from
the bottom up to the lead plate. There's a
magnet that's bending it because of its charge.
And as it's being slowed down by the lead,
it's bent more. So that's how we can tell
the direction that it's travelling in. But when
this was taken, when this measurement happened,
they found an electron but with
a positive charge. So it was the first evidence
of antimatter. And so one of the big questions
we have in particle physics is where did it
all go? Another question we have is, why is
the strength of gravity so small? So you might
think it's quite strong. If you fall down
some stairs, which I wouldn't recommend doing,
but it, you know, it would hurt. But actually,
a magnet can resist the whole strength of
gravity when it picks up a paperclip. So actually,
that's a really small force. And we don't
know why. But actually, that's something we
definitely don't cover at CERN. It's a question
but it's not something we can address right
now. The antimatter-matter asymmetry
is something that's being mainly looked at
by the LHCb experiment, which is one of the
other detectors that's on the LHC ring. But
the Higgs and the dark matter is something
that ATLAS and also CMS are looking for, as part of our studies. So just quickly,
I want to talk about the Higgs boson. So you
may have heard about this particle. It is a particle
that is, well, so the Higgs field is what
gives mass to particles. So, this is a cartoon
illustrating a story about a politician in
the UK that asked for the Higgs field to be
explained. And the story goes that there's
a party and somebody boring walks through
the party with all the guests and nobody moves,
nobody interacts. So the guests are the Higgs
field and the person that walks through it isn't very interesting and so
doesn't talk to anybody, is a light particle
because they don't interact with the field.
And then when somebody famous so for example,
this politician they were trying to impress
walks through
the party, then everybody wants to talk to
them. Everybody wants to interact with them
and when they do, it slows down
their journey through the party. And so in
that case, the interaction with the field
slows them down and this is the way that
they acquire mass. So I've also got an animation
that that helps with this as well. So this
is the Universe without a Higgs field. So
we have quarks, and we have photons that are
moving around at the speed of light. All around.
And then when we introduce the Higgs field,
the quarks which have mass gain mass from
from interacting with the Higgs field,
and so they slow down but the photons which
don't have mass keep whizzing around the Universe.
Okay, so the Higgs boson then is the interaction [of]
the Higgs field with itself, an excitation
within the Higgs fields which creates this
particle. And so it's the measurement of the
Higgs boson, which confirms the Higgs field.
And so here is what it looks like in the ATLAS
detector to potentially measure a Higgs boson,
we can never say for sure what we're getting
in our detector. But in this case, we have
a collision, or we have multiple collisions,
because you can see each one of these dots
is a collision point because
we have whole bunches of protons, but one
[pair] of them collided together. And they created
something which then changed into four muons.
And these four muons, their mass was reconstructed,
and it gave about 125 GeV, which is the mass
of the Higgs boson. And so we can say that
in this case, it's a candidate Higgs boson.
We think it was a Higgs boson that was measured
here. But how else do we view it
as particle physicists? So this is the same,
we call it a channel, it's the way that the
particle changes in this case to four leptons.
So muons are leptons, and over time we collected data.
So this increases as we collect data.
And the red and the purple are what we call
background, it's events that are not the thing
that we're looking for. And you can see here,
these black points, which are the data, the points
that we measure, and let's just pause it a
second. Oh, let's let it finish. Oh...
that's what I didn't want to happen. Pause. Okay,
so these black points are the data, the actual
measurements from our detector. And the coloured
blocks are the simulation that we predict.
So the red and the purple are the simulated
background, the things we're not interested
in. And you can see that these black data
points had a bit missing. Until we added our
simulation of if there was a Higgs boson with
a mass of 125 GeV. So when you add that in,
then it says, "oh, look that matches". So we think
this is what is happening here. Okay,
and we also found it in other channels, and
these are all added together. And on the 4th of July 2012, this was presented in the CERN
auditorium to a very crowded auditorium and
also very crowded CERN, because there were
many people outside of here. And it was really
a moment of celebration, because after a very
long time of searching our data, we could
say from our data that we had found a new
particle, and it was consistent with
the Higgs boson. And here if I zoom in, then
you can see... if you... so this actually was the New York Times front page on the 4th of July
and here's my face! I was a PhD student
at the time and it was such
an exciting moment, I actually slept, with
some friends, outside of the auditorium from
about midnight the night before, in order
to be able to sit in this room to hear those
presentations and to have the confirmation
that we had discovered a new particle as a
as a global team. And so it was really exciting.
The atmosphere was like a rock concert!
We had films on our laptops and snacks and
pillows and bedding and we stayed up all night.
I think the presentation, if I remember right,
was nine o'clock in the morning. So we were
there for a long time waiting to get in.
But it was worth it. And it's a
very special moment in my career history.
Okay, so then a year later, then we got this
announcement and I want to show you that excitement
that it felt. And this is now when the Nobel
Prize was announced.
[From the video] This year's prize is about something very small
that makes all the difference. The
Royal Swedish Academy of Sciences has decided
to award the 2013 Nobel Prize in Physics to
Professor François Englert at Université
libre de Bruxelles, Belgique and Professor Peter Higgs
at University of Edinburgh, United Kingdom
and the Academy citation runs "for the theoretical
discovery of a mechanism that contributes
to our understanding of the origin of mass
of sub-atomic particles, and which recently
was confirmed through the discovery of the
predicted fundamental particle by the
ATLAS and CMS experiments at
CERN's Large Hadron Collider.
[crowd cheers]
So this room, this building rather is ...
actually the cafe, over here,
of what's called Building 40 at CERN, and
it's where many of the physicists working
on the ATLAS and CMS experiments have their offices.
And so they did a livestream of the
Nobel Prize announcement. And yeah, it was
just, it was wonderful to have all of this
hard work acknowledged in that way. So you can
see the enthusiasm there. Okay, so I'm going
to wrap up soon I realised that this was a
whirlwind Introduction to CERN and ATLAS.
But I hope that you enjoyed it. And maybe
if you have some questions, but just quickly
to say, for the road ahead. So what are we
doing now? So we discovered this new particle,
the Higgs boson. It's really important
to do precision measurements of the Standard
Model to really check that is definitely the
Higgs boson that is predicted by theory. So
we really want to collect as much data as
possible and to analyse it as deeply as possible
to see if there are any deviations from the
predictions as to what we measure. Because
that would give hints that maybe there are
some other interactions taking place,
that we haven't been able to measure before
because they happen so rarely. So precision
measurements are a really great way to thoroughly
test the Standard Model. And to really check
that everything is happening as we expect it [to].
So far, it's very resilient. But we are trying
our hardest. Yeah, and then we also have this
search for dark matter. So there are many
ways that dark matter could show up in the
ATLAS detector, or the CMS detector at CERN.
And so, we are we are looking for any of those
cases. So for example, if it travels for some
way through our detector before it changes into
the Standard Model particles, then this would
have a long track with nothing measured and
then suddenly, particles appearing in a different
part of our detector. So that's that's one
way that you could say, okay, something happened
in our detector, that doesn't usually happen
with Standard Model particles. That's one hint
of dark matter. And there are a lot
of innovative physicists who are working out
ways to try and discover dark matter, perhaps
through machine learning techniques. So going
through the data, and seeing if there are
any anomalies that could hint that there is
dark matter in our detector. And then maybe
there's even something new. I mean, there
have been particles that have been discovered
in the past that were not predicted, but they
showed up in the measurements. And
so we have to analyse all of the data that we
collect to really see if there's anything
else happening that we haven't thought of
before.
Okay, and what is happening at CERN right
now? So obviously we have the current
global pandemic, so CERN is prioritising the health
of its staff and the people on site so there's
almost nobody on site right now. But as I
said, many of the people who can work remotely
so I can do my analyses at home and I can
measure and continue to search for the new
physics, with our data from home. So
we are working but we're continuing to
be safe and to prioritise the public health.
But when it is safe to do so and when we
can, we will continue... because actually the
the Large Hadron Collider is off right now.
And so we are not running the accelerator
and this was scheduled to be a period of repairs
and upgrades to the detector, to the accelerator.
So when it is safe to do so we will continue
those upgrades and then we can continue our
next run of
taking measurements with the Large Hadron
Collider. Okay, so that is the end of my presentation,
I really hope you enjoyed it. I'm gonna stop
sharing this screen,
so that now I can go back to the chat.
So, we have some time for questions and I'm
just actually gonna move this over here can
you still see me, I guess you can.
Ah ha! Yes... now I can see me.
But now I can see the chat. So if anyone has
any questions. Then, I will answer them and
as I said I will have to end quite strictly
just before eight o'clock so that I can go
and do the clapping.
Okay, so I'm just going through to try and
I haven't had a chance to read the chat.
Oh yeah and I should definitely say that if you
enjoyed this chat and if you can, then it
would be really great if you could go to the
fundraising link, and give a donation to Mermaids
because it's a really important charity, and
it would be really great to support them.
So, I can see that Julien asked is machine
learning heavily used in analysis of the data
and if so, when it has been used?
So, yeah, machine learning is something we've
been using for a long time. And so, it's,
we use techniques called boosted decision
trees are quite common in particle analyses
particle physics analyses, and we use it to
complement our physics analyses. So we
really have to... you have to think about the
physics first. So you have to think about
what you're looking for and how it will show
up in your data. But we can use boosted decision
trees for example to learn the features of
the new particle, for example, that we're looking for
from simulations, and then it can separate,
what we call the signal from the background.
So this is a way to then be able to... because
one of the problems is that the particle that
we're looking for and the type of lighter
particles that it changes into
can be very similar to other particles.
And then also when I was explaining about
the proton, and how we don't know exactly
which part has collided. All of these, and
that there are multiple collisions happening
at once, we get what are called jets in our
detector. So these are particles that create
a sort of spray of new particles that are
measured in our detector. And these can come from other collisions and they can come
from things we're not interested in,
and so that can then mean that the thing that
where I realise this balloon is going in and
out of focus...
there's not really much I can do about it. Sorry.
And, yeah, so the the signal that we're looking
for can have a background that looks very
similar. And so the machine learning can sometimes
be used to have a better separation of those
two, so that we can say this is more
likely to be signal and this is more likely
to be background. And then something that
I started working on recently is called anomaly
detection. So it's used, for example, in fraud
detection in finance. So, if you're trying
to look for fraudulent transactions in the
credit card, and then you could use anomaly
detection, machine learning algorithms to
learn what is nominal, and then
to look for these fraudulent transactions.
So in the same sense, our new physics that
we're looking for could be 'fraudulent'
type, it's not fraudulent but you know it
could be the same as somebody using your credit
card; it's slightly different and unusual to what
you're used to seeing. And so the anomaly
detection algorithms we can train them to
learn what the Standard Model looks like and
then try and set it on other... on the data
to try... and it's like the lighthouse it could,
it could point in one direction and say, "this
is interesting. This is what we want to look at over here."
So Mike asks what's the likelihood that dark
matter contains any of the Standard Model particles?
So it's not likely because we have
measured them all.
And we would then see it in... so, we know
how they interact and how they would look
in space, I'm not an astrophysicist. And so,
if it was Standard Model particles, then,
we would be able to see it also in space.
So it doesn't interact in the same way, it's
mostly gravitationally. And so we don't see
it for example by being able to see it in
the optical spectrum. So I think. Not likely.
And so Erinma asks, How do you account for
the act of measuring observing things impacting
on what can be observed? Is it true that you
throw away lots of data? So yeah we throw
away so much data. And we do have one stream
of data that is just randomly collected, and
that's to make sure that we haven't thrown
away anything potentially interesting.
So we do check that data sometimes to make sure
that there isn't something in there that we
haven't thought about before, to make sure
that, yeah, we haven't thrown away something
potentially interesting. So we do collect a
small random subset of the data. And I'm not
sure I understand how do you account for the
act of measuring observing things impacting
on what can be observed. So I think this is
that when it goes through our detector that
this then changes the particle. So, yeah,
we have to, when we're measuring in our detector
for example in the calorimeters, the
parts that measure energy, we have to stop them
before we can, they have to deposit
their energy, to be able to measure them.
And so, in this way we are changing the
particle and so it's, we don't necessarily,
we don't measure all of the energy in the
way that we stop it I don't think I've explained
that very well but what it means is that,
then we have to look at very well known particles
that travel through and measure that energy
and then we can calibrate our detector to
make sure that we are getting the correct
measurement.
I hope I answered that question.
So Amber asks what projects are you working
on specifically in ATLAS. So I'm quite unusual,
I think, somewhat unusual. I started off as
a detector physicist, so as I said in the
talk, I was measuring, I was designing
and testing prototype pixel detectors. So
it was actually a new type of pixel detector that was being tested to go in the ATLAS
detector. They're called 3D silicon, and the
main difference between them and what was
in the detector already was that for the original
pixel detectors they had the electrodes on
the surface and 3D ones they had like columns
that went through the detector. And so this
just made them, what we call more radiation
hard. It means that they
will last longer in this very high, energetic,
environment,
at the very centre of the detector.
And yeah, it was a success, and they are in
the detector, in the ATLAS detector,
so that was really nice. And then for
my first postdoc I still did pixel detectors
but then I started working on the Higgs boson.
So I was looking at when the Higgs
boson changes into two tau particles and making
this measurement to see if it is happening
at the rate that we expect it to. It's quite
a difficult measurement to do because tau
particles don't like... they're the heaviest
type of... so we have electrons, muons and taus.
So the heaviest type of leptons, and they
either change into electrons or muons [plus neutrinos],
or they can also change into jets and sprays
of particles. And so they're quite messy,
taus, and they're quite difficult to measure
correctly, but because they're the heaviest lepton,
we expect them to interact and to be created
in this process with the Higgs more often than, for
example, muons or electrons. And so we... it
was an important measurement to make but it
was quite tricky. And so for my first physics
analysis that was quite a tough one. And then
I moved on to studying top quarks, these are
the heaviest quarks, they're actually heavier than
the Higgs boson is. And so, the interaction
between the top quark and the Higgs is also
really important measurement to make... Google
thinks I want to talk to it. No.
And, yeah, it can tell us a lot about our Universe
so I was looking at how the top and the Higgs
interact together. And now I've moved on to
sort of rare top processes, and I'm also doing
machine learning studies to try and find
dark matter. So I've gone really from the
very heart of the detector to quite, you know,
to machine learning, and physics analysis
so it's quite
a change within the field of particle physics.
But it's all been really interesting.
And I've enjoyed all the different projects
I've worked on.
So Jim asks now that the Higgs boson has been
found, what are the big questions for particle
physics? So I mentioned dark matter and dark
energy. What else? So I mean, the difficult
thing now is that we're in uncharted waters.
So before, we had this particle that we wanted
to find and it was almost certain with the Large
Hadron Collider that we would find it, or
we would not, and that wouldn't rule it out.
So it was, it was quite nice when we had the
Higgs boson to look for, because
it was a very direct thing to test. Now as
I said, the important thing is to really measure
it, as precisely as possible, so we haven't
yet finalised all of the measurements, we haven't...
We're still testing it changing into different
particles, and that tells us whether it's
interacting and behaving how we expect it
to. And so these are the precision measurements.
Otherwise, I mean we know so dark matter
is a big one that we're looking for because
we know that it's out there. And so trying
to find it is really important. We also, yeah,
just we're measuring everything to try and
see if anything new comes up because there
there could be something hiding in our data
that we haven't found or haven't even
thought about and so it's really important
to analyse everything as carefully as possible,
and see what else is there.
Oh, so Amber says, I'm working on my first analysis -- oh, great! --
a search for long-lived particles. I really
hope you find them, Amber. That would be wonderful.
And Julien says, what's the status of the hundred
kilometre loop has it been approved? And so
there's no no final decision yet. And there
are a few different proposed... So, this is,
Julien is asking about the next particle accelerator after the Large Hadron Collider. So this is
the FCC the Future Circular Collider, they're
not great at naming things, I will say that
it's there's been no final decision yet it's
currently being discussed, alongside other
proposed accelerators, potential accelerators,
such as a linear Collider in Japan, or also
at CERN, and also circular Collider in China.
So, there are a number of options and they're
all in the discussion phase. So we're not
sure yet.
And I'm glad that Erinma I got your...
that you're happy with the answer. So Eric
asks, how large is this random stream of data
compared with the other more specialised stream?
So it's a really small, I should know the
number but I don't work it's called the triggering,
so I don't know exactly the numbers, but it's
a very small set of data. So it's not
enough that we could, I think, that we could
really discover something with it but it could
tell us whether we should have collected that
data and then in the next run we
could add that in specifically. So, I have
one question. Can you share a bit about the
social life at CERN? So right now it's rubbish. But
I think that's true for most people. It's a really nice atmosphere at CERN.
When I was a PhD student, we, so we have three
restaurants, some cafes, at CERN, and so
it's quite common, when we're not in the current
situation for people to hang out in the
restaurant after after work, to have beverages.
And we have a hotel on site, it's not fancy
but it's where people can stay when they're
visiting CERN for measurements. And, yeah,
it's a good social life, we have a
lot of clubs and different groups, different
communities. And so, yeah, it is actually
it's like a university campus. There's lots
going on, usually. Okay, so I think I am
going to have to wrap it up because I wanted
to make sure that I'm done.. Ah, Amber when
you move back, come say hi! So, if I'm around
too we should have a drink and hang out. Yeah,
so I'm going to wrap this up thank you so
much for watching! I'm gonna leave the video
up so people can watch it later. And if there
are more questions I will try and answer them
at another time. If you can support Mermaids
with the fundraising that would be really
wonderful. Thank you so much for joining.
It's been really fun talking to you and thank
you so much for all of the questions I really
enjoyed answering them.
Yeah, and hopefully see you around either online
or one day, when we can, back in person. Okay.
Thank you very much! And, yeah, take care.
All the best!
Now I have to work out how to end the stream.
Oh, I know how I do it. Okay.
