Hi, I'm Jesse Dylan.
This is my cohost Priscilla
Cohen and this is Jesse's Office.
Today we're talking to experimental
physicist Maria Spiropulu who worked at
CERN's large Hadron Collider and was
on the team that discovered the Higgs
boson. We talked about
matter versus anti-matter,
particle physics as art and the text
message that changed the history of
science. But first, please
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the bad and the ugly. Not the
ugly, but the good and the bad.
Did you ever go down in
the mine? Not again. Well,
I went back a few times since
you, since we've been together,
What is that neutrino experiment
we're talking about? This is a,
the Deep Underground
Neutrino Experiment. DUNE.
It's a huge 72,000 thousand
tons experiment that we'll
be observing interactions
of neutrinos with the liquid argon.
And it is a first of its kind for scale,
magnitude and for the construction
of the sensitive volume.
What is the detector? Right. So
this has never been done before.
We have smaller scale
experiments at Fermilab in
order to test the technologies.
They're called MicroBooNE and different
kinds of names and they're preparing
results of neutrinos.
But the big scale one is the one that
can detect neutrinos from supernova.
So from the skies, observatory. So it's a,
it's like an astronomical observatory,
you can call it like that,
but also it observes handmade neutrinos.
But what is a neutrino
neutrinos? Well, neutrinos are.
Talk about the complication of measuring
neutrinos because they're streaming out
of the sun. And why it's important.
Yeah, and why it's important.
So the neutrinos, everything we theorized
about neutrinos forever was wrong.
The first thing we knew about neutrinos
are they're zero mass particles and they
are partners of the electron,
the muon and the tau,
the leptons that we have
in the standard model.
We thought for the longest of the
times that this would be zero mass.
However, we found that they
actually have tiny masses,
but we didn't measure the masses directly.
We inferred that they have masses
because the oscillate. To think about it,
how to think about it, it's
quantum mechanical oscillations.
It's like one kind of neutrino and another
kind of neutrino are changing as they
move in space into the other part.
The way we say it in physics is that
the mass eigenstates and the flavor
eigenstates are not the same, so
ah, am, a neutrino of a definite
flavor does not have its own mass.
So neutrinos are made of
different kinds of masses.
So one neutrino, neutrino one let's say,
is made of a little bit of a electonr,
and a little bit of muon and a little
bit of tau neutrino. And then when you,
when they propagate through material,
through the earth, through space,
they oscillate into each other
and why is this important?
This is important because it's quantum
mechanical oscillation and mixing of the
neutrinos might be the answer,
might give us an answer if we measure it
precisely of why we have a universe and
not an anti-universe or we have a universe
and not pockets of anti-universes in
there. Why the universe is
matter dominated. Once we
say, you know Feynman said,
it doesn't matter if we say plus or minus,
right? We say matter and antimatter.
We have it. We have measured
matter and antimatter,
but the universe is dominated
by matter particles,
not by antimatter. What
is anti-universe? Exactly.
It will be a universe that
was made of antimatter or.
Give me a metaphor that I can
hold on to in my small brain.
Antimatter we produce and antimatter
is produced in various reactions,
but all the universe, all the
stable universe is made of matter.
When matter and antimatter interact,
they annihilate and energy comes out.
The universe is made of matter with
the definition that we have of matter,
made of electrons, not antielectrons.
We can produce antielectrons.
They, they're called positrons and
we study them and produce them.
And they exist in bound states
and various other configurations.
But they if, if the,
if there was an anti-universe there
would be an anti-Priscilla and when you
shake hand with the anti-Priscilla
energy would come out and there would be
nothing left. So wait. So there's nothing.
So basically it's an
invisible universe? Or? You,
our universes made the,
I made this a farfetched thing
where we can make science,
science fiction universes
that exempt the universe.
And it doesn't matter what we call
universe and anti-universe. The thing is,
is that it's made of only one thing.
It doesn't make, it's not made of both.
So we don't have in our universe
anti-galaxies. We have galaxies.
So neutrinos are streaming out of
the sun. They're everywhere. They,
they cloud our, they cloud our vision.
We don't know what happens to them.
There's sort of a mystery. So, so you're,
so you're building an experiment
that starts in Chicago
and then you build, you beam
neutrinos that you make. South Dakota.
To South Dakota. You've been
there. And then you've dug a mine.
You know in an old mine. Wasn't it a
half mile down below? No it was a mile.
A mile. A mile. Which we all went.
The mine was two miles. Yeah.
The original mine is two miles,
but the cavern is at the one
mile, the underground level.
Now what was it like when
you went there to see?
Because we went there to see
it. We went there. You went.
And we're walking by the old miners with
the dust. Wait, let's just, hold on,
let's just like for the audience. We go
to this obscure place in South Dakota.
It's sort of, it felt like secret
government thing, but it wasn't.
We have to get in these special outfits
and we get into an old elevator.
This is the fearful team. We get into it.
Old elevator and we'd go really slow
a mile down in an old hundred year old
mining elevator. And the reason
we're down there is so that we,
that this experiment is
not contaminated. Correct.
What's the quietest
place on earth. Exactly.
So that it's not radiation contamination
where you've got cosmic rays that are
produced from protons and other particles.
They hit the atmosphere and they
create showers of particles.
So the first particle physics we
did was that, was cosmice rays.
High energy cosmic rays. We had,
we know that there is places
in the universe where the,
where particles are being accelerated
in magnetic fields and so on,
so they come to the earth,
they shower on all the experiments
that we have at the earth levels.
My experiment now at
Caltech, if I go and measure,
I will hear tick, tick,
tick and it will be cosmic rays and then
I have a rate of these kind of events.
But I don't want these kinds of events.
I don't want to have a lot of bakc,
this kind of background.
I want to have as little background as
possible and this is why I stick it down
the earth, those huge
neutrino experiments.
So when you walk through the tunnel,
the deep dark tunnel that's under there,
I mean it feels like you're back in,
you know, olden days and then you get to,
there's a couple experiments
already there. Yes. And,
and you come to a room that
looks like you're in 2001.
What did you, what did you think
when you first experienced that?
What was that like for you? Well,
in this cavern there was
already an experiment, uh,
that had observed, uh, uh,
the difference between what we
expect from solar neutrinos and,
and uh, what we see
more than 50 years ago.
And so the, that old
cavern existed already.
The new cavern tha we are
building, we are excavating.
And so we're going a hundred
feet a day. Detonation,
excavation of the,
of the land of the and the
stone is granite and so on.
And do you go and do painstakingly in
order to get the huge cavern that you will
fit the detector in
there. In the meantime,
at CERN we have build a huge but
still not at that level experiment,
which we call protoDUNE, prototype DUNE.
And we build it in collaboration
with CERN. So you see, we keep,
we keep the exchanges even though
CERN is doing a large Hadron Collider,
we keep the exchanges on
neutrino physics as well.
How did you become interested in
science? You know, like you're,
you're in Greece, you're, you know,
what are you doing and how do
you get interested in science?
And then how do you, what moment do you
realize you're actually really, really,
really, really, really good at it?
Right. As you know, as I get
older, the more I think about it,
the more it's mysterious. Some.
Was it inevitable? I don't know.
It seems to me inevitable now.
Was it random? I don't know. I
don't come from science, science,
family at all. You wanted
to be an astronaut, right?
I wanted to be an astronaut.
I wanted to be a fighter pilot and then
end up NASA and Air force was not taking
females. Oh, that, bad mistake on
their part. But there are females.
They've rectified it. But
since then, of course,
there are females that are,
uh, that are doing that.
And I watched them because I
was like, ah. But, uh, but I,
I was, you know, I wasn't ah,
I wasn't lamenting the fact
that I went to physics. Physics,
I liked it a lot. I liked, I liked
the humanities. I liked the arts.
I wasn't very good in
the arts a little bit.
I could understand it and I could feel
it, but I wasn't good in producing it,
doing art. But I was very
good in math and physics and,
and doing experiments
and taking things apart.
What moment did you understand the
standard model? Understand it is probably
I was, I was 12 or 13. Yeah.
And I was understanding the notion of
the standard model because I was reading
papers in Scientific American about
beyond the standard model. I was, I was,
I was reading about supersymmetry, eh,
between the ages of 12 and 14.
I was obsessed with what
are these particles that are
not the electrons and the
quarks that we have
measured. You know I was,
I was doing that same thing except it
was with Led Zeppelin you know what I
mean? What is the standard
model? Right, the standard model,
which is the standard theory.
So the standard model is a,
is a remarkable, initially
mathematical construct,
but the models,
the physical reality across 24 orders
of magnitude of the subatomic particles
and their interactions and the
standard model of particle physics,
um, which was developing the six days.
We didn't need to measure all the
particles in order to formulate it.
And then from the 60s to 2012 we had
predictions and we were finding the
particles with the last one and the most
difficult and the most elusive being
the Higgs boson. So what is the large
hadron, hadron, colli, collider.
What does it do? What is do? Right now
it does nothing. Well, what did it do?
It's resting. What did it do,
when you guys met? Nobody will,
we'll start doing, we have,
we are expecting to start in about a
year and a half and we will have what we
call run three very, coming
after round two, run one.
Large Hadron Collider has been designed
since 1980 something in Lausanne.
It was approved. And what is it?
It's the extension of the Tevatron,
which was the Collider we
had in Batavia, Illinois,
which doesn't anymore exist.
The Tevatron was colliding
protons with antiprotons. At
an energy that arrvied to 2 TeV,
close to 2 TeV and then we have a
jump of the energy in the Large Hadron
Collider that goes to ah, 14 TeV,
70 V per beam. And we're not colliding
particles and antiparticles,
protons and antiprotons.
We are colliding protons with
protons. Good question is why.
It's because to make
antiparticles and keep them and,
and keep them on these
energies, is very difficult.
Antiparticles are not in
their natural form, right?
You have to manufacture them and then you
have to tend to them carefully so they
don't annihilate with particles.
We did at the Tevatron particles with
antiparticles because in order to get to
the Higgs that low energy,
the processes that we needed
were particle with antiparticle.
For the LHC in order to get to the
Higgs and supersymmetry at those high
energies, good enough to have
particles with particles. In the end.
It's the gluons that collide
at these high energies.
So it's the glue that keeps
the quarks. Yes, you have.
We have still quark quark and uh, and
interactions that have, are of this type.
But in the end it's the
glue. It's the energy.
I thought she was speaking a different
language, I'm not following. So, did you,
do
you remember the first time you,
you went there, you went in,
and you actually went down in the tunnel
and what was that like? Yeah. Yes.
I went many, many times and I was,
and I wanted to be going there
because it was a, I was getting there,
the lecture, you know, in my head,
why are we doing this and how,
the scale and the magnitude and
how many people are working there.
Even when there were the technicians and
engineers and everyone and students and
uh,
and figuring out that we don't have leaks
of water in the underground caverns.
Yes, I was going there. I went there.
Cause how big is it? It's
18 miles around, yeah? Yeah,
it's 27 kilometers around. So from the 4
miles we went to 18 miles. And did you,
did you ever go around the
whole loop underground?
At C? No. I have done the Tevatron
the the whole loop, at CERN,
I'm not even sure that one
can go the whole loop around.
There are all the extraction
beams, the other beamlines.
So I haven't on the
underground, on the top,
I have gone from different access
points. I have gone down to the tunnel.
You know, so, when you first turned
it on there's it, it, you know,
doesn't go so well, correct?
I was there and it went very
good for the first 10 days.
I was there taking days, I was really
quite quite good. And then, um,
and then, you know, like
10 things went wrong,
a transformer blew up and then we replaced
it very fast and something else went
wrong and something else went
wrong. So we went for the first, uh,
10 days it was okay. And
then, uh, September 18, uh,
2008, eh, we blew it.
What happened is, is that there was, uh,
some sort of an implosion and the helium
that we have to keep the magnets cold
that is, that went around,
it caused a huge explosion and it blew
the magnets apart in the place that it
happened. But it's like an explosion
explosion or is it?Yeah. An an, yeah,
an implosion. Like it, like it
took it offline for a year. Yeah,
it took it offline and we have to
rebuild it. And it was good that no,
nobody was there because it
was cold. I mean liquid helium,
it was cold down there and it was like.
Um, then you get past that and um,
you have to revalidate all of physics
and that takes like two years.
And what's that process? Nine months.
We did it in nine months. So what does?
With half of the beam. Right.
In nine months we validated a
hundred years of particle physics.
So how do you go about
doing that? You know,
is it like let's start at the
smallest unit and work our way up?
Yeah.
The way you do it is now you know the
physics because you have discovered it at
the Tevatron right and left.
So you know what you want,
what you expect to see. You design the,
the, the fish net, properly
we call it trigger,
to fish the events that would give you
the W boson, the Z boson, the top quark,
taus, the J/psi,
the various particles that
we have discovered for a,
that we kept discovering for a hundred
years. So when we have the beams,
we're just designing how to
fish all of these processes.
All of this phenomena.
Yeah. Because we know it.
What we didn't know is where's the Higgs?
Essentially the, the collider is
a camera. It's taking pictures,
like millions of pictures
of giant pictures.
So I imagine each one of these photographs
has all of the stuff already in it
except how do you look for it?
How do you look for it and see if it's
all in there. What's that process like?
Imagine your camera, for example,
has a filter and only keeps the
red color from all these pictures.
Right? I know what is red. I will put a
filter there and I will keep only red.
I know what is blue, I will keep only
blue. So for us, I know what is the top,
what is the w, what is the Z? What is a
J/psi, I will, I put all these filters.
Right. And they run and
then I take the data,
all of the filters and I sort them.
And very painstaking, you know.
Each one of these events
where we call events,
we've got 100 million
channels, electronic channels.
You're going to see how many of them
fired. You gotta reconstruct the event,
which means of all the tens
of the detectors you have,
you take the channels that
fired, you don't take the noise,
you don't take the pedestal, like the
noise. Right. Something fire, you take it.
Then you have to take all the other,
all the other hits, that fired,
all the other detectors within
the time of this collision.
Timing's very important.
And they come every 25 nanoseconds so
they are not coming like. So, so. Wait.
Yeah. That's really every nano,
every 25 nanoseconds. 25
nanoseconds we've got.
It's a lot of seconds.
So there's essentially the collider is
four cameras and if you find something
you've got to call the person at the
other place and see if they saw it too,
correct?
Yes. They there's two general cameras,
general purpose physics, so ATLAS and CMS.
The other two cameras
are a little different.
The one operates when we have ion
collisions, when we try and do, understand
the plasma,
particle plasma and connects
again with astrophysics.
But ATLAS and CMS. But ATLAS and CMS.
They're, they're different constructions
because they have to see different,
they have to see the same thing
in different ways. Thank you.
This is very good. We call them
dual in some sense, right? Right.
So one has a bigger magnet
and one has a smaller magnet.
One is a bigger detector in volume.
One is more dense and smaller in volume.
But if you work out the details of the
performance for watching the Higgs here
and watching the Higgs there,
the performance has to be such that they
both watch Higgs because you can't have
Higgs here and no Higgs there.
So after nine months you rebuild all
of physics for the rest of us. Yes.
We appreciate that. Yes, thank
you. Appreciate that. We did that.
Now does there come a day where you
decide, now we're going to look for it.
We're going to look for the Higgs?
And how do you know basically there
is a thing that you don't know,
like who says there's something called
the Higgs, but we've never found it.
And why is it called Higgs? Yeah,
so there is a, there's three Higgs,
three Higgs notions. There's the
human Higgs, Mr. Peter Higgs,
who got a Nobel prize for the Higgs.
And what was the Higgs that he got
the Nobel prize for? It was, uh,
the Higgs particle, which is,
is a vibration of the Higgs
field. Like every, every,
the way we talk about particles and
particle physics, we talk about fields.
There is a field, there's the electron
field. And then if you tickle it,
electrons come out, the particle version
of the field. You tickle the particle?
You tickle the field, particle
comes out. Very cool. Okay. Okay.
Let's just stick with this one
part about the Higgs, right? Yes.
You decide on one day you're going to
look for the Higgs. Well, we've been,
we've been looking for the Higgs
the Tevatron forever as well.
It's just that we couldn't do the
tickling with the energy we had.
It wasn't enough. There was a few Higgs
produced, but it was very little. Right.
So at the LHC was like, a lot of.
Large Hadron Collider for anyone who
didn't know what that meant. Right.
Large Hadron Collider.
So what is the Higgs,
it's a very old thing that we think,
you know, everything else comes out of,
so describe it. So the Higgs
provides the Higgs construct,
the mathematically and the
physics, the theory of it.
Provides the symmetry breaking mechanism.
And I will explain that because it
sounds like a, it sounds like ah,
alien language.
The symmetry breaking mechanism
that when it happens I go from,
I go from symmetry to less symmetry.
And in this, in this, um,
transition,
it's a quantum critical phenomena
in this transition happens mass.
So before when I am in a symmetrical
universe from the point of view of the
interactions and the forces,
no particle has mass.
So what is this kind of universe?
This is the universe that we don't know
what it is. We haven't measured it,
right?
But we expected that there
would be something which
is called electroweak phase
transition where there
is symmetry breaking.
And I go from a massless universe to
a massive universe through the Higgs
mechanism, which is the symmetry breaking.
Now what kind of other
symmetry breaking we have,
the best examples of symmetry
breakings are in solids, in crystals,
and magnetic materials where
if all the spins are aligned,
magnetic materials, it has one property.
If you, if it becomes disordered,
it has another property
in one exhibits magnetism,
and the other doesn't exhibit magnetism.
And there's different kinds
of translational symmetry
in crystals that create,
when they break, when the symmetry
breaks, it creates phonons.
You could study all of that in crystals.
People have been studying this for
centuries in well but for a long time in
solids.
But we never studied that and the quantum
vacuum because that's the Higgs and
because it's difficult.
So the Higgs is the equivalent of symmetry
breakings that we understand where
when something goes from a, eh,
a very symmetric to a less symmetric
place, a phenomenon occurs,
whether it is a particle, a spin wave, a,
a phenomenon occurs. So. It's a, it's a,
without these kind of a critical
phenomena. The supersymmetric,
a symmetric, and let's not confuse
it with supersymmetry, but a sym,
a symmetric universe where we
didn't have the quantum transition,
we didn't have the symmetry breaking
would be a boring non-universe.
It would be nothing. Is this like the
big bang? I mean. No, no, good question.
The Big Bang is, we don't know what it is.
So right, but but what, staying on the
Higgs. We are staying on the Higgs.
Staying on the Higgs. In a simple way,
it's like thinking that you have a puzzle
that's all together and then when you
put it through the collider, it breaks
down into all its component pieces.
And that's really never been observed
before except in this thing. Correct. So
you go about starting to revalidate
these pieces at one moment and obviously
it's a big success, right?
But there is a moment where you and
maybe three or four people are the only
people on the earth that know
about this. Yes. And, and.
12 people in that case. There's a
picture of that. Can you, can you,
can you tell, well you weren't actually
there. You were somewhere else.
I was in. But can you tell us.
I was, I was in the Cold Harbor teaching
oncologists how we do
background in particle physics
so that they can figure out
in their research how we think.
How particle physicists think.
So. So you're at, you're
at CERN you say, listen,
I gotta go and you guys
do some work over here.
Take us through the story of what
had happened and what that was like.
Right.
It was 12 June and it was a 10
o'clock in the morning at Cold Harbor
laboratories there. And so one
of my postdocs at CERN, uh,
starts typing on Skype,
chatting with me and it
says, it's there. It was.
So my heart was losing bits. There
was no, because, and also I was very,
I was very nervous because I
wanted to see from the numbers,
is it enough signal over background
so that we can say Eureka.
And then he went from one
channel to another channel.
He was telling me the numbers
and I said, I want the plot.
Did you do the mass fit? What is the mass?
So we had this exchange and the,
and the time for my talk was coming,
so I said, I'm sorry, I can't give the,
you have to reschedule me somehow a
little later because I have to tell you
this. We have the Higgs.
The, the, this experiment
thousands of people worked on, you,
you led one of the teams of
these two teams and, and uh,
uh, what did it feel like? I mean,
it's like that says the center of,
of our understanding of what
the, the standard model is.
And you're, you know, you can go all
the way back to, you know, past Eins,
past Einstein to, to think about
this. You're a part of history.
Like what did you, what did you and
your team think about at that moment?
Yeah. Eh, well, I mean the team, the,
especially what I called the kids,
the ones that they're between the ages of,
because we had even some
undergraduates were, were working,
they were not there in the room,
but the 22-year -olds and all the
way to postdocs, 30-year-olds,
eh, I think there was no. The
enjoyment came much later.
Right?
So you have the focus now that it's
almost like you're saving lives and it's
fight or flight. We have
to prepare the slides.
The slides go to me from me they go to
the spokesperson from the spokesperson to
the director of CERN. Comparisons
are happening and, and uh,
the paper is being written.
So at each level we have,
everyone had had to keep the focus.
I think even the director was,
maybe the director had a
moment at that time that, uh,
that felt enthusiastic. But it is,
the spokespeople of the experiment
from for CMS was Joseph Incandela,
um, from Santa Barbara and
from ATLAS it was Fabiola
Gianotti who is now the director
general and a good friend of mine.
And even the spokespeople were very,
very focused and calm. Um, because you,
you still have to, you
have to be sure. Right?
You can;t say to the world, I discovered
the Higgs and then take it back.
And in hadron physics,
the culture is such that you don't do
oops mistake because it's a hundred years
of producing it. It's what you said,
the validation, the validation,
the validation. There's no
oopsie. There's no. But what.
Wait, wait, wait,
once it's discovered and you've seen
it and you've captured it, is it,
can you put that away and move on
or are you still looking for it?
In other words, once you've been
able to define or how to find it,
can you go back and
find it again and again?
We're going back and we're still going
back and find it again and again.
In different kinds of final states,
we didn't discover it in all its
possibilities that can be discovered.
So you, it also, you know, it,
the predictions had it having certain
characteristics of which it had most of
those, but also had other
things that were mysterious.
And we'll take another 20 or 30
years of physics to figure out.
Yeah, we still, the curveball is
still there. It's ma, the mass is a,
is a huge mystery. In fact, in the
70s, Politzer from Caltech and Wolfram,
Wolfram from Wolfram,
they had written a paper that in this
kind of symmetry breaking field and
mechanism, eh,
you can be in an unstable minimum and
then you can quantum tunnel and the entire
universe will bubble away and appear
in a different minimum with a different
kind of of um, uh, vacuum energy,
let's say.
So the Higgs at the moment
because we only know it's,
we know, we measure the mass
and we measure the couplings,
who the other particles,
how it gives them mass.
We have not measured how it couples to
itself, how it generates mass for itself.
You have to think of the Higgs also, when
I say symmetry break. Male and female.
It's self-propelled. Yes.
So this is self-propelled and it's okay,
touches everyone else and
assigns mass to everybody else.
But it touches itself to produce mass
for itself. And it has a big mass.
125 is a big, huge mass that it has.
So the 125 number in, when,
when the theories are making the theory,
the 125 number is not there in the theory.
This is like a latent parameter
of the model could be 114,
115, to 120 and 170 etc.
And people are writing papers. If
it is that, then that if it is that,
then that. And the problem with 125 is,
is that it's very difficult to figure
out with 125 how to make the quantum
corrections to the mass of the Higgs fit
so that all the puzzle is together and
it's hard to say that supersymmetry is
going to give you this answer for this
particular mass of the Higgs.
So now you are in no man's land and you
can't say this isn't the Higgs because
you measured it and you keep
measuring it in one and the other,
but the curveball is there.
How are we going to figure out
what is going on with this mass?
So, you know, Feynman said, we're up
against mysteries. Yeah, it's a mystery.
And do we,
how do you think about science when
you're just sitting around and you're
thinking about these particles and you're
thinking about these components and
these pieces and you
know, how do you think,
how do you visualize it in your mind? You
said at the beginning, well, I wasn't,
I didn't, wasn't able to do the arts,
but isn't this like the most art that we
have in society? You know what I mean?
Besides Beethoven, isn't particle
physics actually the most artistic thing?
We as a species actually do?
We, I, thank you for saying
that. I really think so. Eh.
I think the way our,
all particle physicists,
the way our brains work and the way
we conceptualize things in terms of
designing new experiments because it's
the mysteries that we want to solve.
We kind of cover so much space of what
can we possibly build and how we can
possibly catch the shot in the dark.
And so I do think that with,
with machine learning and
AI, if we put together,
imagine that if you put together all the
knowledge of all the experiments right
now, the incompatibilities,
some of the results that
they're incompatible,
you can spot them and maybe
you can, you can have the,
the,
the compilation of all
knowledge machine-wise give
you a better design of an
experiment faster. We come to that, right?
In one century we came to
designs that they're ingenious.
But imagine if with machine,
with machine learning,
with all these new
methodologies that we have,
because we have the data and the
knowledge and the computing power,
it is possible that we can design
apriori the experiments and not to,
you see we can design an exp,
we can have an experimental design apriori
that it is optimized in a much better
way than we can artistically
do it with our neurons.
Looking at things like, you
know, Kip's, you know, gravity,
you know, and you know some of
the things we see, you know,
deep in the universe with
different experiments and you know,
you have all these different things
going on and how do they, is,
how do they interrelate?
Is that what you're?
Yes, we can do that.
We can interrelate the,
after the standard model
of particle physics,
we build the standard model
of the, the, the model,
the standard model of cosmology.
Now these two are interrelated
because one we're talking about,
you mentioned big bang. When we're talking
about the dynamics of the universe,
how it creates, created,
how it behaves in the scales that we see
in particle physics and how it's going
to evolve.
You've got to put all the data together
and the puzzles actually just brick,
teasing out all the puzzles and
mysteries that we have already.
And it's getting bigger. Like
ALMA. Yes, exactly. ALMA this,
the two days ago I saw on the, some
results from this observatory in Chile,
this site of observatories in
Chile, and they found galaxies,
old galaxies that are close to
how old the universe is. Well,
that doesn't fit what well with the
standard model of cosmology that we have,
with large-scale structure,
etc. So puzzles in terms of ah,
particle physics and cosmology,
persisting puzzles, eh,
the connection of the Higgs with
dark matter. What is dark matter?
Is it a particle or is
it some quantum thing?
What is dark energy? What is the,
the universe filled with this, uh,
with this ambient energy.
And as you said, expanding,
Priscilla, expanding and
accelerated form. But you know,
we've been observing this for a
hundred years. Maybe it will contract,
maybe it will do something
else. I mean, the,
the reason why the big bang is a picture,
became a picture, is because when
you observe the universe expanding,
it's a very appealing thing to
do a back-polation and say, well,
it's expanding. Then it started
it from here. Right. It's a very.
Is that our need to understand that and
also why is it called the God particle?
Oh yes. Is that? Uh, because,
because Leon Lederman wrote a book that
was called the Goddamn particle and he
said it in like. The Goddamn
particle? Goddamn particle.
And he site editor said.
He said the headline editor says I'm
not publishing the Goddamn particle. Oh,
you mean because it was so frustrating
and hard to find? Not that it was. Yeah,
it was so hard to find, so and
then, and then the editor said,
we can call it the God particle
and it will include the notion ah,
lean on, that it is a Goddamn
particle, but you know,
it's. Sort of led to a lot more problems
for us. Yeah. Everybody believes in it.
So, so, so they call it God.
Everybody believes in it,
nobody has seen it up
to then. And uh, and uh,
it creates all other
particles. So yeah, it's um.
So, so artificial
intelligence, usually when we,
when we talk about
artificial intelligence,
we're talking about semantic search
engines, like doing very, you know,
selling you stuff or you know, not
very, uh, substantial. Sophisticated.
Not not, so when you're saying
science and artificial intelligence,
what are you talking about?
So the scientific method, you know,
Francis Bacon said, you do an experiment,
you have a theory, you test. If the,
if the data is, uh, is showing
you what you theorized,
then it's good. And if it doesn't,
it doesn't matter how beautiful the
theory stays and how brilliant etc.,
you junk the theory and
you start from scratch.
Well that was up to now, up
to 21st century, 21st century,
we have arrived at immense computation
power and it's a Looper if you think
about it because where does the
computation power comes from?
Comes from simple things like the
transistors that are based on quantum
mechanics. Right. Switches that you
can then do zeros and ones and compute,
computer engines are created by physics,
without computer engines now they have
become extremely powerful and without
them, how are we doing
physics, science, any,
any science eventually
that has data. Right.
Now the 21st century is
the end of Moore's law.
Where we are, we are, we are in the
upper fallacies of computing power.
You cannot put more transistors
in a chip, but now you have
tons of data, scientific
data, you have data,
you can produce data in the number of
emails and tweets and do other stuff and
do your, and do the, the advertisement
that you say. But the data,
the scientific data we have is the most
useful data because for the sciences
that we understand, we have a theory,
we have the labeled data because we have
a theory for the science that we don't
have a theory, we do data-driven, but
they have tons of data imag, biogenetics.
Imagine all the people who are, um,
translating to the mapping the genome
for every human being. This is,
this is, this is, ah Googles of data.
The, the biggest data that I
know so far that is useful data,
it comes from particle physics because
we were at the petabyte per second.
We are being, our input is that, and
now it will be 50 petabytes per second.
So when we did that, when we
started taking data at the LHC,
we have our own networks, our
own pipes to, to send the data,
our own computing engines. We could,
we would have broken the
Internet if we tried to do that.
So now with all this data and all
this compute power you can put in,
um,
you can put at work algorithms that people
developed in the 70s that tried to do
clever computations as the brain because
the brain is the biggest computer of
all and with the lowest power, right?
So they used, uh, uh,
that's why they're called
neural networks, right?
So now you've got the algorithms also,
and the algorithms learn from the data.
This is not a very, this is
not a very foreign thing.
This is like the babies or the neurons.
They learn from the experience,
the touch, the reinf,
they reinforce the knowledge from their
environment and now you can start and do
hot houses of learning, right?
So you learn very fast because
you've got a lot of data,
total hot house, hot house,
and you prepare results based on
learning from the data and then.
And it's more data than a human being
can analyze. Absolutely. I mean,
and it's more even than, uh,
a machine without the algorithms would
be able to compute, you know, with the,
the old way of computation.
So AI for us in science is to accelerate
the discovery and also to give us new
insights, big scale
simulations, the hardware,
the software, the data, and the
algorithms is a new ecosystem.
All of it together. I'm not separating it.
And it's part of the scientific method.
What is going to happen when you
turn a quantum computer on because
it doesn't exactly, it's
not just that it's faster,
it's that it thinks very
differently than our computers.
So what do you hope happens
with a quantum computer?
Right,
so when the quantum computer
turns on and the idea where,
why Feynman and Deutsch,
and others were thinking of the quantum
computer long time ago is this because
the universe is quantum in its core.
So if you really want to
know the universe, eh,
precisely, then only with a quantum,
only with a system that is quantum you
can know everything of the universe.
You cannot know everything of black
holes without a quantum system.
But we don't know the
physics of black. People,
people struggle with the physics of black
hole up to where it is quantum up to
where it is a gravity, general
relativity, if you'd fall in,
if you come out, but spaghettification,
movies, etc. But we really don't know.
We do have beautiful photograph
of a black hole. We do.
We do have a beautiful photograph
of the black hole from the,
from all the data of all the telescopes.
And it was as of recent that we
have that. And it's quite ah,
quite impressive, yes. What does the
world look like with quantum computing?
How's it going to change?
Yeah, we don't know. I mean,
the quantum quantum
computing aspirationally is,
as just said we're gonna run.
So we're done with Moore's law.
We can not put more transistors
on a chip. We're going to make,
um,
we're gonna make computing that can be
done at its basis in parallel threads,
not just GPUs that we have in parallel.
We have parallel computing with GPUs,
but at its beginning, in essence,
because of quantum superposition,
we can have paths that are,
that are in parallel being
solved very fast from the,
from the very beginning, right? So you
can do compute very fast like that.
And then you have a very
peculiar phenomenon,
um, of, uh, of quantum physics,
which is quantum entanglement.
And the two of them can
make powerful, secure,
faster computation. Uh,
if we can build this machines at scale,
maybe we will build smaller machines
of qubits and network them and,
and still kind of reap the benefit.
Uh,
but at the moment we don't know what
is a quantum computer at the moment.
If we have an architecture. So,
you know, for the normal computers,
we know it's silicon,
right? Sure. For, uh,
for the quantum computer.
Will it be atoms that you will put in
some place and then compute on the atoms?
Will it be ions?
Will it be superconducting little
circuits that all of these have?
The qubit has this two states. And,
and then this is why it can encode a
lot of information because it's not zero
and it's not one, it's
everything in between. And uh,
and so all of these
physical systems can be,
can do computation. But how
large, how big, you know,
how many thousand atoms do you need or
how many millions qubits do you need in
order to do the computations? And
which architecture do you have?
Do you take the ions? Do you take the
atems to take the superconducting qubits?
We have many physical systems. So,
this is why why don't we talk
about quantum computers today,
we talk about physics experiments and
then we talk about systems integration.
And then we talk about scaling.
And all of these need not just physicists
because it's a physics experiment,
but applied physicists, theoretical
physicists, mathematicians,
applied mathematicians, how
the computer will work, um, uh,
engineers, quantum engineers. We
didn't have quantum engineers.
When I went to grad school we
didn't have quantum device,
a class that is quantum devices.
Now if you go to every university,
there is a quantum engineering track
and there's quantum devices classes.
But how does this change the world? Like
how does the world look differently?
This is the kind of
question that, you know,
50 years ago there was this
book that was written, um,
with essays from all the people at MIT
that the people who are doing computers
and the visionaries of the future,
and the people who were imagining that
you could sit on your laptop and have all
the information at the tip of your finger
and do your tax returns and talk to
everyone in the world. And,
uh, they put this essay,
they put this set of essays,
especially for computing,
most of it was right on.
But then they didn't ask,
how is this going to change the world?
Am I going to be hacked every
time and have, you know.
You gotta think of unintended
consequences. But why?
Because they didn't make a round
table with the social scientists,
with the philosophers, with the
historians, with the artists. You can't.
And in fact, there's a,
there's a historian at Harvard and she
wrote a little article in the New Yorker
a few months ago. That was impressive
because when they asked that,
she goes through the detail of what was
in the book and then when they asked the
mathematicians and the
physicists and the engineers,
so how is this going to impact.
I don't know. We'll see.
Right. So this is something that one
needs to sit down and, and think through.
More anxiety I would, I would say
is at the top of the list. Well.
We can't say, but, but it would be good.
It would be good to not do it
post factor to not think the,
you know, because,
because right now the
unintended consequences are
hitting us 50 years later and,
and we, we take everything for granted
that it should be the way it is today.
So are you optimistic for
the future of science?
It's going to be, um,
yes, I'm very optimistic.
It's going to be fantastical.
It's going to be better than
science fiction and weirder.
And weirder? Yeah. Well
it already is. Great.
Well thank you Maria so much
for coming in. This was great.
You have to come back, there's lots.
I'll come back. Yeah, that was great.
Thank you for your questions. The
validation question, Jesse, you know,
I will put you, I will put
you into review committees,
because this is the question always that
we have to be careful about science,
validation and verification,
again and again.
While you deal with that in the
social sciences too, where you,
where it's ambiguous and you can
never get a, you know, the, the,
a microscope is Twitter, you know, the
co, we have the collider called Twitter.
You know what I mean? Like, you
know, puts a lot of information out,
but you know, you can't separate signal
from noise. You know what I mean?
Yeah, no. And, and, uh, and the
more and the more network that is,
there's more noise
because you have all this,
all these unintended consequences from
having bots and automated system and they
inject so much noise.
So the pipes are now mostly noise
and very little useful knowledge.
Well that's exactly right. And that's a
metaphor for what's going on socially.
Yeah, it is. It is.
great. Thank you, Maria. All right.
Yay. Thanks guys. You're amazing.
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