Hello, and welcome to the Physics World weekly
podcast.
I'm Hamish Johnston.
In this episode, we meet Sarah Alderweireld,
who is a physicist working on the ATLAS
experiment at CERN,
the world famous physics lab that straddles the
Swiss French border and is home to the
Large Hadron Collider
or LHC.
The podcast
explores
how the huge ATLAS detector
is used to study the high energy collisions
of protons
and sometimes
lead ions
at the LHC.
In conversation with Physics World's Margaret Harris,
Sarah explains how physicists deal with the vast
amounts of information
produced by ATLAS.
Margaret and Sarah also chat about the ongoing
high luminosity
upgrade to the LHC
and its experiments,
which will be finished in 2030.
And they also talk about the challenges and
rewards
of working on a very long term
scientific project.
Here's that conversation.
My guest today is Sarah Aldoworlds,
a postdoc at the University of Edinburgh in
Scotland and a member of the ATLAS collaboration
at CERN, the European particle physics laboratory.
Hello, Sarah. Welcome to the podcast.
Hello.
Perhaps you could begin by telling our listeners
what ATLAS does and what your role is
within that.
So ATLAS is a large detector
at the Large Hadron Collider,
which is built as a general purpose experiment.
And we try to zoom in on interesting
collision events that are happening when the LHC
is on,
in order to study both our understanding
of the standard model of particle physics and
look beyond it to see if we can
find signs of new physics.
And what's your role within that? Because ATLAS
is a really big collaboration. It's got hundreds
of physicists working on it. Absolutely. It's even
thousands.
I am in my current role as postdoc
working on several analysis,
mostly in the searches area.
And I also work on the detector as
a trigger expert,
which deals with,
the decision making life as the collisions are
happening
to decide which ones we record and which
ones we give up on because we don't
have the bandwidth to study everything.
And then in parallel with those two hands
on efforts, I'm also a coordinator
for the Higgs multiboson
and supersymmetry
searches group, which is about a 500 sized
subset of people that are all looking into,
searches for new physics.
Yeah. What does searches actually involve? You know,
talk me through what happens when the collider
is operating. You know, what's what's your your
daily work look like?
So when you imagine processes happening in nature,
which are then also the ones that we
can try to create with the the accelerator,
you expect
that certain processes happen
more frequently than others. And we have a
very good description of nature in the standard
model, and so we have a prediction of
how frequently we expect these things to happen.
What the detector then does is testing
whether if we look at the the collisions
we're actually seeing and we analyze them, we
identify them as a certain thing,
whether this matches with the prediction we have.
And in on one hand of the measurements,
we have the very precise measurements of the
standard model where you verify
that you are getting
things right with this prediction. And on the
other hand of the word, there are the
searches
for things that lie beyond, because we have
signs from, for example, astrophysics as well, that
there are things in nature
connected to dark matter or tensions in other
areas,
where there has to be a little bit
more than we have in our standard mobile
prediction.
And then from small deviations in places or
maybe
tough to catch
patterns in in the detector,
there could be a hint that this has
to have an explanation in new physics because
if we only had the standard version, it
wouldn't be there. Then what we do is
on one hand, we optimize the detector to
be as as thoroughly covering as possible in
all of these potential signatures
and then record the data. And then when
we have the data, often these things happen
in parallel on, like, the previous set while
you work on the next one,
you develop algorithms,
classic ones, but also
using modern techniques to
zoom in on
what is in this dataset. You put your
prediction,
we call this the background, and then you
look at the the signatures that you could
potentially see on top of this.
And then we make the the statistical prediction
of, how well these things agree. And as
soon as you find something that doesn't agree,
that's when it gets exciting.
Now you talk about seeing and searches, but
it's actually been a long time since people
were literally seeing what's happened in a particle
collider. You know, you had the cloud chamber
days where you could see particle traces and
collisions.
What does it involve to, you know, sort
of say, oh, that event is interesting. Let's
let's look at that one. Let's save that
event. How does that process work?
This gets back to the the trigger work
I was mentioning
where,
for the ATLAS detector, this happens in several
phases. You have the level one system and
the higher level trigger system, and then offline
processing can continue a bit more even.
And
in the level one system, you use custom
hardware because you have to take decisions ultra
fast,
and it's so fast that you don't even
have time to read out all of the
information that is in the detector. You just
take crucial parts of it that help you
in this decision making. You make a first
decision.
And then in the second step,
say something was really energetic
and it had
two object flying in two different directions,
and,
that matches one of the things we're interested
in. And you can zoom in on those
blobs and look at the precision around them
in this second layer of trigger algorithms which
happens in
software, and that then gives you the more
precise decision, which can allow you to filter
better again which events you really want to
keep, and those then get passed on for,
offline analysis.
And in that same process,
we also run the algorithms that try to
identify
the different elements of a collision that we
know. So you can try to find the
electrons, and you can try to find,
the heavier particles, maybe the standard model bosons.
And, actually, in connection to how in the
past things happened with the bubble chamber and
we actually looked at the snapshot,
now in the software, we also have ways
to visualize this. And we're talking about data
analysis with
numbers of events that is way too large
to manually look at everyone
individually.
But if we're interested in a particular one,
we can visualize it and bring this up
and actually zoom into it and look at
it as well.
What are some of the specific events that
you're you're looking for that you would get
really excited if you saw?
So personally, I'm a supersymmetry expert.
And the idea of supersymmetry
is that, if you take all of the
standard model particles we know, there would be
an a duplicate set of supersymmetric
particles, and they all line up one to
one with some
parameter changes, of course. And this could then
explain various open questions that we have, about
how the world works.
And
because this is quite a well developed
theory model, it also allows to to make
predictions
of what these signatures would look like, if
they were there.
And a lot of them go hand in
hand with something we call missing
transverse energy.
Because when you have a collision in the
detector or you you have a collision and
you record it with a detector,
energy that comes in also has to go
out. And because our detector is constructed to
be all covering or as much as possible,
if you have things flying in two directions,
those factors have to sum up.
And if they don't, then something is missing,
and this missing thing could be an invisible
particle.
And there are some particles in in the
standard mobile version of the world where they
are invisible, but they're usually
not the dominant part of of processes.
In the under standard model physics, you have
many more particles that could be a lot
heavier that might have interactions that aren't typically
visible in our detector because they don't interact
with materials in the same way, and they
would leave much larger
amounts of missing energy in our sums. And
so we look for a lot of the
searches, we look for signatures with lots of
missing energy.
Now regular listeners to the podcast may remember
that this is kind of a transition period
for CERN. We had CERN's next director general,
Mark Thompson, on the podcast in January talking
about plans for the lab's long term future.
And then back at the March, I spoke
about visiting CERN, and you were one of
my tour guides on my visit, actually,
and just learning about plans for the next
upgrade of the the Large Hadron Collider.
What's it like to work at CERN during
this this sort of period of transition?
This is an absolutely exciting time to be
here because it's
wonderful to be able to be not only
in one aspect of high energy physics, which
is already cool in itself, but actually
three or even more parts. And when I
say three, I'm thinking of, on one hand,
we have data
that has been recorded over the past ten
ish years of LHC,
and we can
make analysis with it and learn more about
physics.
And then in a second element,
we have plans for the next
n years.
It continues quite far, but let's start with
the first part, the phase two upgrade for
the high luminosity LHC.
This will start happening quite soon with the
long shutdown in which we turn things off
and we make quite sizable upgrades to the
detectors.
This means that these detectors have been in
design for
a number of years already. And right now,
we're actually starting to get the components that
are the final ones and putting these together.
Some examples, for example, are currently coming together
in, like, the big development hall next to
where the detector sits above ground.
We get to work on those, test that
it all comes together correctly. It works on
the surface level.
And then
once these come together, they will go down
to the detector,
and then get put to use. That's the
the actual hands on
building the detector.
And I said the upgrade continues very long.
Even beyond this upgrade, we're thinking about the
next ones already, and this then involves detector
design and thinking about what technology will be
available and how can we use it to
to make the best possible detectors in future.
And so these three phases really bring together
all of the possibilities
for
research in physics.
And
it goes in cycles. And right now, it
just happens to be one where you really
get hands on connection to to all of
the parts.
What are the biggest challenges associated with these
tasks, particularly with the upgrade?
Timelines are always a a tricky thing, especially
because they are so extended. And you need
experts of many different types. Like, we need
engineers. We need
people who understand the physics to to connect
with the engineers and say, like, okay. Yes.
That is high techno high important technology, but
it might not do exactly what it is
we are interested in zooming in and on.
We also need students to be there to
learn some of these things so that it
can continue,
later on. Then you need people who are
in touch with outside who
get
to see how maybe data analysis algorithms
or detector technology gets to evolve also in
other places and keep feeding that into what
we are doing right here.
So it really brings together a a lot
of people.
And that's also one of the things that
makes the CERN campus a very interesting place
to be because it actually has good seeding
ground here to come together like that.
You're an early career researcher. So, you know,
maybe in contrast to some of the lab's
senior leadership, you're likely to be around not
only for the HiLumie upgrade, but for whatever
comes after that and even beyond, as you
say, the next n years.
What are your thoughts about that? Do you
think that far ahead? You're just more head
down, focused on the immediate task?
I think there are two parts to that.
On one hand,
also because nothing is ever guaranteed in this
field,
you do want to focus on the now
and see what you can do now and
and do the best you can.
But on the other hand, I think if
you stick around in in any research field
for long enough,
you start to see the bigger picture and
you do want to be a part of
it, and you have the ideas of
this might work better than that. I can
see how globally this evolves, what other people
are interested in, And then it becomes a
puzzle of of bringing together and chipping in,
like, the little bits where I maybe am
the expert.
And
I would say
I started thinking about the future already,
say, when becoming a postdoctoral researcher, so after
finishing the PhD.
And
we really are talking long time scales because
if we talk past HLLHC,
I will be close to retirement age.
And that makes it then also connect with
teaching and and mentoring and supervising and and
making sure that the knowledge is spread
because
I can do what I can, and I
would love to continue doing it. But I'm
also very aware that we will need the
next people after that because fundamental research,
does not happen in ten seconds.
Because I guess also with the with just
the process of building a detector, if you
only do it every twenty years, that is
literally generation, and there's a risk that people
will forget how to do it.
Absolutely.
We
see this even on on shorter time scales
as well where you you quite frequently hear,
but documentation
is very important.
And then you find yourself in the control
room with some tricky problem making everything fail.
And you know, like, oh, I've seen this
error before, but why is it doing this
right now?
And you you look at it for half
an hour, an hour, and you're still scratching
your head after going out for a quick
lunch.
And at some point,
some colleague that hasn't been near there in
in in years walks past, asks you what
you're doing, and you tell them and it's
like,
maybe you want to check this.
Lo and behold, this is always the solution.
So, yeah, we do need long term experts,
but also people who are just keen on
on digging into finicky issues and being creative
with the solutions.
Thank you very much for speaking to us,
Sarah. Thank you. It's been great to talk
to you.
Likewise. Thanks for inviting me.
That was Sarah Alderweireld
of the University of Edinburgh in conversation with
Physics World's Margaret Harris.
We're more than halfway through 2025,
which has been declared the International Year of
Quantum Science and Technology
by the UN agency
UNESCO.
As part of our celebrations
here at Physics World, we've published a 62
page quantum briefing.
The cover of the briefing features a painting
by the physicist turned artist, Felicity Inkpen.
That work is called Qubit's
Duality.
And in a recent episode of the Physics
World Stories podcast,
Felicity shares her journey from academic physics to
the art world,
and talks about the creative process
as she explores the elusive nature of quantum
reality.
Also in that podcast,
Physics World's Tushna Kamasariat
talks about a feature article in the Quantum
Briefing that's called the curious case of quantum
Cheshire cats.
It explores the strange phenomenon
whereby a particle's
properties
seem to be in a different place from
the particle itself,
reminiscent
of Lewis Carroll's
famous feline
in Alice in Wonderland,
whose grin
lingers
even after it's gone.
That episode of the stories podcast is called
painting the unseen,
visualizing
the quantum world. And you can find it
on the physics world website or at your
favorite podcast provider.
And you can read the entire quantum briefing
on our website.
Just
click on the magazine tab.
I'm afraid that's all the time we have
for this week's podcast. Thanks to Sarah and
Margaret for a fascinating
conversation,
and a special thanks to our producer, Fred
Isles.
We'll be back again next week. See you
then.