Hello, and welcome to the Physics World weekly
podcast.
I'm Hamish Johnston.
In this episode, I'm in conversation with Bert
de Jong, who is director
of the Quantum Systems Accelerator
at the Lawrence Berkeley
National Laboratory
in The US.
But first, a message from Oxford Ionix.
This podcast is brought to you by Oxford
Ionix,
an ion q company.
As part of ion q, Oxford ionics is
a leading quantum technology company focused on building
and delivering the world's most powerful quantum computers.
Combining scale and performance,
Oxford Ionix
uniquely uses electronics
instead of lasers to control its trapped ion
cubits.
This enables the company to manufacture
its quantum computers
via the standard
semiconductor supply chain,
while maintaining
world records in quantum performance.
For more information about Oxford IONICS,
visit www.oxionics.com.
Bert de Jong is department head for computational
sciences
and leads the applied computing
for scientific
discovery group at Lawrence Berkeley National Lab,
where he's also
director of the Quantum Systems Accelerator.
Bert's background is in computational chemistry,
and that led him to understand
that quantum physics
can be used as a scientific tool.
He shares that vision with the Quantum Systems
Accelerator,
which is a national organization
with the mission to codesign
algorithms,
quantum devices, and engineering
solutions
that are needed to solve
scientific problems.
Hi, Bert. Welcome to the podcast.
Hi, Amish.
Thanks for having me, and I'm looking forward
to talk to you.
So, Bert, you're the director of the Quantum
Systems
Accelerator.
Can you describe this initiative?
What are its aims, and who are its
members?
So,
the Quantum System Accelerator is one of five
national quantum initiative centers that is funded by
the Department of Energy,
out of the basic energy
sciences office.
Our mission specifically
is to really
move technology forward. So,
we have as a mission to deliver,
advanced prototypes
in atoms,
ions, and superconducting
qubits,
but also building,
additional
technology infrastructure that allows us to scale. So
we do a lot of work with integrated
photonics, a lot of work with, controls.
And all of that together, those prototypes that
we're delivering,
as part of our program are then used,
not just built, but also used to do
science. And and our ultimate goal is is
to use these prototype types to deliver
scientific advantage to a point that,
we could solve problems with our quantum prototypes
that could not be done on classical computers.
I see. And and,
obviously, your national lab is, is a member
of the QSA. Who are some of the
other members?
So we are a team of, we're consisting
of two national labs that are driving this.
That's, Lawrence Berkeley National Lab and Sandia National
Laboratories,
together with about another 14 partners.
And those are,
the academic partners, I mean. So they're Harvard,
MIT,
Colorado,
Caltech, and many others. So, we're about 450
people that are working on this project.
Now this is not just,
National Labs in academia.
We're also
having a a a good level of partnerships
with commercial entities.
Some of the technology we have been developing
in the first five years
have drawn a lot of attention as I
mentioned already the integrated photonics.
We actually developed these chips. Sandia fabricates these
chips, and,
companies like,
Atom computing,
Quantinium,
Quera,
which we have much bigger and, longer,
collaboration with already, and I and Q are
very keen to take those technologies and explore
them, try to see how they work because
that allows them to scale. And this is
an example of us looking kind of technology
forward,
kind of doing
research that is a little further ahead than
most companies would be doing at this point
in time. That's part of our mission too
as we are here to to explore
new technology,
kinda
take a high risk, high reward type approach,
and eventually help us derisk industry,
as they advance the technologies.
But yes. So we're about fifteen, sixteen institutions
of on the science side.
We have about
eight or nine companies that are working with
us,
on different levels.
I mentioned the integrated photonics, but there is
also a large interest in in working with
us on the application side because they're all
interested in in getting to an quantum advance
or scientific advance, as we would like to
call it, but also helping and partnering on
on some of the fundamentals like integrate
like controls, for example.
And, Bert, one of the focuses or foci,
should I should I say, of the QSA
is,
the development of algorithms
for quantum processors.
What are the current challenges in this area?
Is it difficult to develop
specific algorithms
when it's not quite clear what qubit types
and architectures
will be used in the first
large scale quantum computers?
Yes. We definitely have a component of of
developing algorithms. We actually have also a component
of effort focused on error correction.
I would say this is one of the
reasons why we have not
chosen a specific technology.
We we've gone with
building prototypes for atoms,
try trapped ions, and superconducting qubits
because we really are focused on what do
we need to do, what algorithmic work has
to be done to make sure that these,
prototypes, these technologies can deliver on department of
energy science.
So the biggest,
I would say, what we have seen so
far, which is which is an interesting observation
in the first five years is
that the areas we're focusing on are high
energy physics,
or nuclear physics. They are very similar in
in in style,
chemical dynamics,
and many body physics. What's interesting is so
far is that we've been able to demonstrate
similar types of problems on all three technologies.
And each technology
approaches these things slightly differently, and that's fine.
It allows us to kind of do an
early testing of, is this technology going to
be something that is going
to be important to the Department of Energy
for the future?
So far, the three technologies that we chose
to to take a
a effort in are all
demonstrating that they have a path to deliver
on scientific advantage.
The neutral atoms, honestly, when we started, neutral
atoms was kind of not really there, that
they had the first small scale demonstrations
of, oh, we can actually control and harness
atoms.
During the first five years of our center,
we delivered systems that are 256
cubits.
The technologies that we developed have shown up
effectively in a in a company like Quira.
And so our
collaboration with Quira is very closed right now
because,
their technologies
the system they're delivering right now or producing
is kind of based on technologies that that
have a root in in the quantum system
accelerator.
There we go next with atoms, they're talking
about 100 logical qubits.
Not that full fault tolerance, but at a
accuracy level
that is enough for us to do science.
And I think this is where the the
trick comes in is that when you're talking
about developing algorithms, it's not as much just
building algorithms and hoping the hardware catches up.
This is really a co design process.
What we may need on the algorithmic side
or the application side
might drive or might give us opportunities to
really pursue,
slightly different,
approaches within the hardware technologies to make it
happen.
And and another example for that for that
for that point, the other interesting sample is
is, the work that we're doing with with
trapped ions. We've taken a very different tact
there in scaling, and that is instead of
going to two to the n where you
have each,
add I and effectively being a,
a qubit, we're actually really focusing right now
on on the,
on the coupling between the atoms, which allows
us to get another set of degrees of
freedom, which means we can go to six
to the end, maybe eight to the end.
So that's a very different way of actually
approaching this. What's nice about it
is,
it provides us also access to both for,
fermions and,
bosons,
which is really where most of the science
is going to go. For example, the high
energy physics, we are really looking at a
dynamical process of hadronization.
So how do actually
particles we have in the universe form?
That's a dynamical process.
In chemistry, we are looking at same thing.
What is the chemical dynamics process? How do
how does charge? How does
mass move through a system?
Those are the really relevant questions we wanna
tackle.
A ground state calculation is not where
our community needs to focus on because that's
not the relevant science problem.
With the exception of many body physics where
we always try to find new phases of
matter, which often end to be end up
being,
kind of
ground state properties of very complex systems. But,
again, all three, we have been able to
do science with
all three platforms have been able to do
science in all three those technologies
really through co design. We are we are
not just building a prototype, somebody builds a
prototype, and
the algorithmic developers, oh, we'll have to figure
out how to use it. It is really
that that
joining of those two,
skill sets or all of those skill sets
together to make it happen.
And, Bert, are are you one of those
people who
I mean, do you think that, ultimately,
there will be one
type of qubit that is used in
most quantum computers in the future?
You know, that one qubit technology that ticks
all the boxes?
Or do you think that we're going to
see hybrid systems
in the future where oh, I don't know.
We've got some ion qubits that are used
in some part of the calculation and superconducting
qubits in another part and,
maybe
a linear optical system to do something else.
Is that how things
look like they're shaping up?
No. I I would so one of the
things that I
I'm do not believe in is that, there
is going to be
a one type of technology that's going to
win at all, at least not in the
near future. Maybe in the long term future,
but I think the technology is still nascent
enough
that,
there is no clear winner. Yep. Again, the
atoms were way behind. The atoms right now
are way
ahead, I would say. And so and there
is lots of dark horses in the race
at this point in time too that haven't
reached the threshold yet,
but could get there.
And so
I would say there is a lot of
opportunities for different technologies to be there. And,
honestly, if you think of it as,
as we try to now think about it
as a future scientific instrument,
there might not be one instrument that does
it all. Now we have at the national
labs lots of different instruments, large scale instruments
we built,
and they all have specific purposes.
So I rather see the technologies being complementary
to each other, not working together.
When you talk about hybrid, I think differently.
If you talk about hybrid, I think of
the need to integrate with high performance computing,
technologies,
and that is definitely going to be the
case.
I don't think a quantum computer will be,
standing on its own and be able to
operate on its own without
some level of high performance computing behind it.
This could be all the way from,
actually compiling, building the programs that need to
be run on these systems
to doing error correction, to doing post processing.
All of these
aspects, especially
decoding and and so on,
seems to be heavily,
reliant on high performance computing, and
I have a sense a lot of this
might eventually also rely on AI.
So, honestly, what I see more when it
comes to a hybrid system, I see a
convergence of of quantum technologies with high performance
computing and AI to deliver a platform. And
for us, that means, in the words of
Dario Gill, our undersecretary,
a scientific instrument
that is going to,
deliver
new knowledge,
new discoveries,
that are critical for the Department of Energy.
And, Bert, I wanted to ask you about
another important focus of QSA,
and that's to harness the exotic properties of
quantum matter to create new technologies,
possibly even new types of qubits.
Can you talk about some of the r
and d that you're supporting when it comes
to,
quantum matter?
So,
mostly, when we talk about quantum matter, we
are actually using the technologies that we're developing
to investigate and study the new phases of
matter. We've done it with neutral atoms. We
have built,
material,
well, simulated materials,
and we're able to probe
new phases of matter.
There is one exception in our center, and
that is also in the atoms, but we're
taking it slightly differently. And that's some work
that we're doing in Colorado where,
we're actually taking atoms
and integrating them in cavities that allows us
to have more degrees of freedoms and effectively
take those atoms and rearrange them and control
them in a way that it behaves like
a new phase of matter.
So we do some of those. We do
it also
using the technologies we have as simulators.
And, really, that's what we are producing.
Even in building those specific cavity QED type
systems that Colorado builds,
they're still going to be all simulators that's
mimic
a quantum system,
in this case, quantum matter that we wanna
probe and understand.
And, also, Bert, I wanted to ask you
about,
the engineering challenges because,
you know, I suppose your scientists are doing
some fantastic,
research. But ultimately,
you know, one of your goals is to,
to work with companies and and develop
new technologies.
So so what are some of the challenges
of creating new quantum technologies, and and how
is the QSA
helping to overcome them?
Well, that depends on which,
kind of qubit modality you're going after. So
we the neutral atoms is a simple thing
of trying to scale.
How can we get more atoms to control?
How can we better control them? So we
have been doing some work on building specific
cryogenic systems that,
have large,
access points for lasers, which is a big
challenge. So this is, something, product that actually
well, product, it's it's a prototype that was
developed
as as part of
Colorado's efforts.
We have demonstrated
how we can control
up now six, seven thousand atoms. We'll be
at at 15,000
soon.
But then you start to run into other
limits, and this is where the what I've
said before, integrated photonics
became an
important thing.
We chose to actually work on that because
we knew we needed to scale.
And scaling is going to be the biggest
challenge for for neutral atoms.
The same with ions. That's going to be
also a a very big challenge. How do
you scale
and be able to sustain the fidelity
and the accuracy
of the qubits
at scale?
Superconducting qubits is a very different story.
There, it's it's really a material science problem.
It's not even a material sciences, materials
engineering
problem.
How can you build these qubits
accurately
the way you would like them from your
models,
and be able to build them consistently. So
not just one qubit that is,
the best of the best and all the
other nine let's say you have a 109
or 99 are bad and one is good.
That is not what we need. That was
our hero qubits that that are not going
to give us anything.
We need to get to a point where
we can build a 100 qubits that all
have these long
lifetime
have very long t ones,
or t two so that they can actually
do many operations.
So with superconducting, it's a very different story.
So we're working with,
companies like, CoLab, which is also,
of course, the home of,
John Martinessa,
the Nobel Prize winner,
and with, Applied Materials,
together with our foundries here, with our molecular
foundry, and with,
some of our fabrication capabilities
to see how we can build better, more
reliable qubits
at scale so that we can actually do
something real in the science
and try to if we see if we
can get to,
many milliseconds,
if not longer lifetimes of these qubits.
So there's a lot of work that is
being done to understand where the defects are.
That's a very different problem on scaling and
accuracy than it is for neutral atoms and
trapped ions. But so we're doing really research
in all of those aspects,
from atoms to superconducting qubits to make sure
that we can get
reliable qubits or
QDits,
where possible
so that we can actually do
designs that we wanna do and deliver on
the ultimate mission, which is,
enabling scientific discovery and quantum advantage.
And people, of course, are gonna be crucial
to this, the right people.
I wanted to ask you about
developing a skilled
quantum workforce.
What what is the QSA doing,
towards that end, you know, in terms of
training people and, and, I suppose,
introducing quantum science and technology
to
a a wider group of people, you know,
not just chemists and physicists
and computer scientists, but other people who are
needed,
to create these technologies.
Yes. So,
well,
of course, as I said, we are 450
people. That includes grad students, undergrads, and postdocs.
Of course, our easiest pathway to to help
build the workforce is to to train students,
grad students, undergrad students, postdocs,
so that they are ready to go into
the workforce as soon as they're ready with
their
their degrees or with their career development as
part of a a postdoctoral fellow.
But we have we believe that that is
not the the ultimate solution
because that's the short term. And those are
also all they're grad students. They're they're
they are physicists,
chemists, but we need a lot of other
skills.
Most of my programs here actually have,
are integrated teams of computer scientists, applied mathematicians,
and and and domain scientists effectively, and I
believe that is very important.
The other thing that I believe is very
important is to start earlier.
We cannot wait till they're in college and
then introduce them to physics, and, hopefully,
they change their minds on where they wanted
to go and actually go and get a
degree that is relevant for quantum information sciences.
So one of the things Q cam what
we have done is we have developed a
program called QCamp.
So QCamp is actually not even looking at
grad school or universities.
It's looking at high schools.
And this is where we really need to
go.
So we have had a program now for
the last
four years
where we are,
doing hands on programs with students and with
teachers.
And we do both
separately, but both because we believe the reach
of teachers is bigger than we can ever
do by ourselves by bringing in students.
But we have,
trained
probably hundreds of teachers now.
Started in California and in New Mexico where
that's where where kind of the core of
our center had been. But now we're at
six, seven states, and our goal is to
go
to fourteen, fifteen states next year,
and reach
the the teachers, reach the students.
What's interesting is that
different states have realized
that there is an opportunity here. And so
be going into new states without
us providing any funding,
the states, governments,
the educational departments in the states are willing
to fund these efforts to bring these teachers
to these hands on programs
and learn basis of quantum so they can
teach it to their high school students.
And, again, we do it also in parallel
with students,
and that's,
I think we've had three, four, 500 students
that we have,
introduced to quantum so far.
Then there is
another
bridge in between, and that is we have
the high school students. We have those that
go to universities.
But, really, where I see a change in
the needs in in industry right now
is that they are looking for a lot
of skills that don't require
a a big degree, an an associate's degree
or a
maybe a bachelor's degree.
But it's skills like how do we, fabricate
large numbers of these quantum computers because we
are selling them, we're moving them.
We need people that can install them, people
that can do the wiring,
people that can work with lasers, people that
can work with cryo and build
power plants for that for that matter to
operate these systems.
And we need people that can code, that
can program these systems,
or
work with the controls,
do electronic controls, electrical engineering type roles.
So we actually are also in addition to
growing our high school program. We're taking that
program to what we have locally here in
The US, which is community colleges.
They are generally AA degrees.
Those are
students that will never hear about,
about quantum. It's not a key part of
their curriculum.
And they don't need to hear a lot.
They need to just know that that's a
job opportunity,
and it's a growing job opportunity.
Right now, I would say
the quantum industry,
one in three jobs gets filled.
That's how big our shortage is, and it's
only going to get worse.
So we need to reach them everywhere. High
school, so they are
ready to go and get a degree that
allows them to go
into the quantum industry. We're trying to hit
them at the community colleges because that's the
opportunities.
And then as part of the center that
we have,
we have twelve, fourteen,
academic partners.
They're bringing undergrads. They're bringing grad students, and
they're bringing postdocs.
So all of those together, you're trying to
kinda cover a whole spectrum to make sure
that we have the people,
ready, not just now, but also in the
future.
And and, Bert, how did you first become
interested in quantum science and technology? Your background
is in chemistry and computer science, so, you
know, it does make sense. But when
when when were you first hooked?
So,
yeah, I can give you a little bit
of a background. So, as I said, I'm
a computational chemist, but my drive is not
just
computational chemistry. I'm just wanna solve scientific problems.
I have a lot of interest in figuring
out how to build better batteries, how to,
generate energy source energy sources that are more
efficient
in general.
For that, as a computational chemist, I use
the tools that I have. So for the
first
half of my career, I focused primarily on
HPC, building
quantum chemistry codes that could scale on exascale
platforms.
So we actually build one of those.
But we know we still have limits because
of the computational methods we use. They fundamentally
are
exponentially,
growing in in the complexity of the problem.
And so
when I came
so I spent most of my time the
first half of my career also at Pacific
Northwest National Lab. When I moved to Lawrence
Berkeley National Lab, I started to think a
little bit more holistically.
So what is next?
If an exascale computer comes, how far can
they scale beyond that?
Are there other technologies?
And so that's when, about
eleven years ago, I really started to look
at, hey. Quantum could be another technology that
I can use to solve scientific problems.
AI could be another technology
that I can use. So
right now, while quantum is my biggest portfolio,
I also have a program in AI. I
have a program in HPC
because to me, it's the I'm building the
tools so I can do the science to
deliver,
scientific discovery. So I got into quantum about
eleven years ago,
really started helped start that program here at
Berkeley Lab, and it has just taken off,
since then. I used I ran a lot
I still run a lot of programs that
are focused on actually the algorithms, the software
side
of building these quantum computers.
But I've gotten myself
three, four years ago involved with, with the
quantum system accelerator.
And then when there's had to be a
transition of leadership, I took over this program,
which is an interesting experience on its own
because I work lot now with experimental physicists,
engineers,
which is very different from the world that
I have come from, but it's also a
very exciting,
a role to have at this point in
time and and when it comes to where
quantum information sciences is going.
And and, Bert, let's say that, you know,
you and your colleagues at QSA,
you know, you're involved in a in a
in a major breakthrough in, I don't know,
creating
a scalable
system of qubits. And all of a sudden,
you have your hands on a on a
very powerful
quantum computer.
As a computer scientist and chemist, what problem
would you want to solve first?
I mean, has there been a problem that
you've that you've struggled with your entire career
and, you could suddenly be able to solve
if you had access to such a powerful
quantum computer?
How many do you want? That's the real
problem, I think. Any problem that we tackle
and the the computational methods that we need
to use to get the accuracy,
they require this.
So,
everybody
talks about
systems like the
for nitrogen fixation.
Turns out that that's not a ground state
problem. That is a dynamics problem. And so
dynamics problems are very much
very hard to tackle on classical computers,
the time evolution,
the complexity of the problem.
So that's
definitely one that I would like to demonstrate
in the short term that we can actually
do the dynamics and understand the real chemical
process
that drives the catalysis,
of a nitrogen
to ammonia.
The other ones that I'm really interested in
is is things like organic photovoltaics.
Those are low energy ones.
If you look at, a lot of needs,
we don't need,
conversion of, in high energy ranges or high
temperature ranges, but rather
do it in low temperature ranges. So
close to boiling water, for example. That is
a small energy range
that you can do with organic photovoltaics.
They are not very efficient right now. Can
we actually use quantum computers to simulate and
understand these processes
and not just simulate them, but then also
combine that
with AI and discover
new
materials,
new organic materials that can do this.
There's also a drive on figuring out how
to handle carbon.
That's now a little bit of a less,
focused area right now simply because,
that is not a priority for department of
energy at this point in time.
But,
my ultimate
would be, can I build a,
so for California,
can I build a desalination
plant that is, energy neutral? That would be
my ultimate mission, which is where it comes
into
how can we
recover materials,
how can we,
store energy that we are generating from solar
during the day. So we need more efficient
solar, but we need very efficient batteries so
we can run this plant twenty four seven.
But, also, how can we recover as much
energy that we use? For example, if we
boil water to, take get the fresh water
out,
how do we cool it down and recover
as much energy, which is where the organic
photovoltaics
play in. So there is a lot of
components.
So my old that's my ultimate dream. Can
I build one that is energy and cost
neutral?
But there is a lot of fundamental
chemistry and material sciences that has to happen,
And those are problems that are too challenging
to solve right now on classical computers.
Well, that's great. That sounds like a very
laudable goal, Bert. Thanks so much for coming
on the podcast
and talking about the QSA and your research.
You're welcome.
This was fun talking to you.
This podcast is brought to you by Oxford
IONIX,
an ion q company.
For more information about Oxford IONIX,
visit www.oxionix.com.
I'm afraid that's all the time we have
for this week's episode.
I'm Hamish Johnston, and our producer is Fred
Iles.
The original theme music for this podcast
is called one three seven,
and it was composed and performed
by the physicist
Philip Moriarty.