Hello, and welcome to the Physics World Weekly
Podcast.
I'm Hamish Johnston.
This episode looks at Quantum Computing
from 2 different perspectives.
Our first guest is Elena Blokina,
who is Chief Scientific Officer at Equal 1,
which is an award winning company that is
developing
a hybrid quantum classical
computing chip.
And our second guest is Brandon Grinkmeier,
who is a PhD student at Harvard University
working in several cutting edge areas
of quantum research.
But first,
Physics World is brought to you by IOP
Publishing,
which is pleased to announce that the journal
Progress in Energy
is extending its article remit
and now accepts original research.
This means that you can publish your groundbreaking
work alongside some of our most impactful
and cited reviews
on energy.
Prge
is a high impact
multidisciplinary
journal
focusing on a wide range of issues
related to the global energy transition.
We invite you to publish with us and
share your work with a global audience.
You can find progress in energy
at IOPscience.
Based in Dublin, EqualOne
makes a hybrid quantum classical computing chip.
It's won the 2024
Quantum Business Innovation
and Growth or Cubic Prize, which is given
by the Institute of Physics
to a small or medium sized company in
the UK or Ireland
that's focusing
on the commercialization
of quantum technology,
products, or solutions.
I'm very pleased to have Elena Blakina down
the line from Dublin.
She's chief scientific officer at Equal 1
and also an associate professor of engineering
at University College Dublin.
Hi, Elena.
Welcome to the podcast.
Hello.
Thanks very much for having me, and I'm
delighted to be here. Thank you. So congratulations,
Elena, to you and your colleagues
at Equal One. And and to start off,
I'd like to ask you to introduce the
company.
When was it founded, and how many employees
does it have today?
Equal One Starshas, and I would say it's
Starshas, in 2017
just from a collaboration.
So, Dirk Leibold,
Bogdan Stashevsky,
and Mike Oscar, so that's the group of
researchers. We knew each other very well.
We start, like, a collaboration. And I I
I also was one of the few researchers
back then working with, like, Dirk Leibold and
Mike.
And, basically, our collaboration was triggered by, new
technology. There was a very new process, semiconductor
process EPID in 2017.
And we asked the question, can we use
this process to build a qubit and actually
to build a
kind of, you know, very affordable quantum computer?
So
as you can understand, from this, okay, so
our company is based on a semiconductor process,
based on semiconductor qubits. And since then, now
if you look at, like, the company now,
it's 36 people across 5 different locations, and,
we are working to build really affordable,
scalable quantum computers.
Maybe just to ash a little bit on
the choice of our technology, because semiconductor is
so common. It's so kind of, absolutely
technology, which is everywhere. It facilitates our information
process,
laptops, like smartphones and so on. And,
so our goal is our goal is to
build and, you know, to help to use
this process to build cubits and integrate
the cubits with,
process in electronics, with control circuitry, and so
on. So to achieve this goal, we started
with an engineering team. So we have, like,
a world leading engineering team. But now with
36 people, we have physicists. We have computer
scientists. We have people who understand how to
build wafers, how to characterize qubits, how to
actually build the cryo mechanical systems to maintain
the low temperature.
And we believe because of, again, this broad
range of expertise within one company, so, we
actually are on track to success.
Maybe, also, I will note that,
working in a deep technology space, okay, like
in a deep technology field,
and being still quite dominated by science and
kind of research and academic groups, yes, we
naturally would have quite a lot of again
recognized researchers in the group, but we also
have people who actually have a proven track
record to bring success and commercialize commercialize silicon
products. So it's also kind of a part
like, very important part of the team. I
see. That's great. So it sounds like you
you you're sort of expanding
out from a a core,
sort of a a core of technology experts
into
a a sort of a a company that
that has people of many talents in it.
Yes. Correct. Yeah.
And and, just,
going back to the technology,
Equal 1 offers a a quantum system on
a chip,
technology. Can you give us a brief description
of of the architecture and how it works?
When we say quantum system on chip, we
imply dash, perhaps cubits themselves, so it's a
core underlying quantum technology.
So you have to have a cubits as
a part of this chip. But we also
need quite a lot of,
classical or conventional electronics because we need to
send the control signals to a quant, to
cubits. We need to sense the cubits. We
need to understand what's the state of the
cubits.
Quantum gates is a sequence of multiple pulses,
so all of that, it requires classical electronics.
Electronics builds on transistors.
So and if you look at, like, again,
at the what's what's actually what's what's the
core? What's the hash of consumers' electronic right
now is an integrated chip where you could
do that all signal process in one device
and one die.
And we believe that quantum systems on chip
will be that core, will be that hot
of a quantum computer in the future. Because,
again, all of these components, we must exist
in the same condition or in the same
space. We need to be very close together.
Maybe to expand a little bit, like, to
expand a little bit, like, why I would
say so, why I would think so,
Just think if you would like to control
all those components separately. Like, think of, like,
a very
first generation of computers, like, any kind of
45.
So you would have a huge diode, like
a tubes, okay, or, like, a large transistors.
And if you want to kind of denage
information processing or control, kind of, you know,
control of all type of signals in the
system, like vape being separately,
it's very difficult to do. And you will
not be able to control millions or billions
of these devices.
So what actually made possible,
to progress to extremely kind of high density
information processing devices is, like, the technology able
allowed us to build the smaller transistors.
Like, we made the transistor smaller so we
could put many transistors on the same proximity
in the immediate proxy machine. So we were
able to build
different logical or controlling blocks, coordination, the work
of these transistors, and that's how we arrived
to integrated technology.
So integrated circuits and integrated technology.
So this technology is now, available for 50
years. There is 50 years of progress in
this technology.
And I'd say I believe DASH quantum
technology is also entering the stage. So I
think it's matured enough so we can begin
to talk about cointegration
cubits
and all of DASH control electronics.
Again, sensing systems, microwave driving systems, a system
that actually must take decision, what pulses to
apply, when to apply,
maybe what pulses must, correct arrows and then
cubits and so on. So I think I'm
gonna look, you know, it's actually really at
that stage.
And
integration
actually is a very difficult kind of you
know, it's a very challenging task. Okay? So,
it's very easy to say, but, like, in
reality, of course, I mean, like, you know,
it's a very challenging task for physicists and
for engineers to do that.
Just think about this. Like, cubes generally require
very low temperature.
So,
we're we're talking about, like, extremely low temperatures,
like few millikelvins and pretty much no thermal
fluctuations would exist. But then when you think
about electronics,
electronics dissipates, consumes a lot of power, dissipates
a lot of heat, and particularly, again, if
you're taking many decisions, taking many measurements, and
so on. And it's very easy to see
because if you just touch a back panel
of the desktop or laptop, you will you
will feel how how much heat is dissipated
there. So combining these trends, like, you know,
very low temperature for qubits, but then on
the other hand, electronic dissipation power, is the
challenge.
But, again, take into account that semiconductor technology
in general and the industry in general matured
enough, we believe I mean, like, you know,
we are in the in the right stage.
We choose
quantum dots cubits because these cubits can appear
at a relatively high temperatures, again, compared to
cubits, okay, not to our normal room temperature.
And we know that circuits can be made
very efficient.
It could be very ultra low power circuits
based on, like, most advanced technological nodes, so
we we can process a lot of information
and at the same time consume less power.
So combining these two trends, I think there
will be a sweet spot, a particular kind
of, you know, point where spin
silicon cubits, which is, again, a type of
quantum dot cubits, will be finally Compachable and
will be integrated for electronics.
And and so that's why,
Equal 1 has has chosen
quantum dot cubits. Is it? Is it the
the the integration?
Well,
I shouldn't I probably shouldn't say ease of
integration,
but but your belief that,
quantum dot cubits,
will be
more easily
integrated into a large scale
quantum computer than, say, superconducting circuits or trapped
ions?
Yes. It's actually a very good point because
in DSH you you mentioned VISTA Technologies, and
in DSH, there are multiple
platforms. Keep the platforms existing today.
And it's very natural to say each will
have its own advantages.
And, again, very natural every there will be
some some some bottlenecks, okay, in each of
the technologies.
But indeed, we choose to work with quantum
dots, and quantum dot based cubits. And again,
sometimes we'll say, silicon spin cubits is kind
of, you know, a type of, the type
of the cubish
because because exactly for this reason. So the
material of choice is silicon.
It's a abundant material. It's a very kind
of it's a very well understood material.
We build classical conventional electronics based on this
material. We can understand, we can use, we
can leverage all of that we know from
classical devices to bring it to a qubit.
And maybe just, again, to understand a little
bit like, to explain a little bit, okay,
what's actually this type of a qubit. So
that's it's not very that different from a
transistor.
So if you
think about, semiconductor materials, if you can get,
like probably the best device to compare will
be a transistor. But, like, if you think
about this, there is just a host material,
silicon material. We take a wafer, and we
will deposit a set of metallic gates.
So metallic gates would exert electric fields. Electric
fields would create, potential
energy wells or potential energy barriers. And if
the temperature is low enough, we can just
trap 1 electrons in those in those wells.
And exactly the same thing happens in the
transistor.
So if you think, like, about the classical
transistor, it's something very, very similar happening there,
except for at high temperature, you do not
charge a single electron. But in cold in
cold temperatures and deep cryogenic temperatures, we can
just manipulate one electron.
So the accuracy of electric signals, the, again,
the efficiency of the circuits is is is
so good, so we can actually really manipulate
one electron.
Now if you add a magnetic field, so
we can actualize spin,
spin of election, and, it's a fundamental quantum
property.
And spin of election is quite is actually,
is a very good example here because
it's a quantum it's it's it's a quantum
state with only 2 projections.
So if you apply external magnetic field, there's
going to be only 2 projections in the
same or the opposite direction of the external
magnetic field, and you will get a natural
qubit here in this case. So with natural
state 0 and 1.
So quantum dots,
cubits, and, like, again, spin silicon qubit, in
particular case of dash I,
is a relatively new platform,
again, compared to other mature technologies.
However, what we can see is the
performance metrics of these qubits keep increasing year
after year after year, just over the past
5, maybe 10 years.
So it means that now we have we
can see very good coherence time. We begin
to see very high fidelity of quantum gates.
We begin to see the metrics which which
are now comparable with mature technologies.
And one of the important notes I want
to make here is I mentioned this, like,
a little bit in my previous answer. So
quantum dot cubits or spilly or silicon spin
cubits can appear at higher temperatures.
So we don't need, like, 50 millikelvins or
100 millikelvins.
There are some examples where a spin oscillation
or kind of, you know, spin
flip can be seen can be seen even
at 1 Kelvin.
So compared, again, to millikelvin
cubit, it's it's actually a big difference.
And at 1 Kelvin, you can build already
quite efficient circuits. So it will allow you
the thermal budget would allow you to build
a quite efficient circuits. So that's, I think,
one of the one of the main reasons
why we work with quantum dots and, silicon
and silicon cubits.
And, yes, the other one you also pointed
out from the very beginning, it's integration. It's
the same, as I mentioned, like, you know,
like, when I was explaining what's actually is
a is a qubit. It's pretty much a
transistor. It's it's very similar.
So it's the ease of, like, you know,
it's like a similarity of the process. I
mean, like, you know, being able to build
very similar devices, being able also to build
sensors to accommodate them, like, you know, all
the,
analog and digital electronics to drive the qubits.
It's kind of, you know, that's, that also,
like, you know, it's a very it's going
to be quite simple in the case of
relatively simple, right, in molecular, I should say,
in the case of spin qubits.
I see. And does that does that mean
that there's no there's no lasers involved, there's
no microwaves
involved like you would have with other qubits?
The the control is all
electronic.
You will require microwave driving. So it's still
I mean, looking off the energy cap for
a spin qubit, it's still a microwave,
kind of new frequency.
So however, again, in conventional electronics, it's not
something unheard of. Right? Because if you look,
like, for example, smartphone, so we are driving
much higher frequencies. Like, we we we are
controlling, kind of manipulating much higher frequencies.
For a qubit, we are speaking about, like,
real, like, RF microwave range. So 5, maybe
10 gigahertz, which is, again, very comfortable,
design range for integrated circuitry. So, Elena, what
challenges did you have to overcome to achieve
the level of integration that you'd like to,
to get to?
Yeah. Okay. It's also a very good question.
A number of challenges, Aureish. Maybe 1, maybe
one follows directly from my previous answer because
I mentioned that we would like to increase
the temperature of the qubit.
If we can a period, let's say, 500
milliKelberts, 1 kelvins, that will be excellent. Again,
that allow quite a lot of analytical thermal
budget for electronics. But that's difficult,
possible for quantum dots, but difficult
because the temperature is something again, thermal fluctuation
is something that will affect the initial state
of the qubit. It will affect, again, in
the, like, you know, the quality of quantum
operation,
coherence of the qubit, or or time when
qubit actually preserves quantum information.
So temperature generally is is is a is
a destroying, this kind of damaging factor for
qubits.
However, what we can see now is the
scientific community is looking into this, and, like,
there's a lot of ideas we can adapt,
we can take from scientific community and research
as well. So there are algorithms how to
help with a preselection of initial states. There
are algorithms to mitigate,
mitigate errors. There are you there is a
very, very kind of, you know, emergent, private
field of quantum error correction.
So a lot of that can be proshed,
to engineering and design.
And I think, again, scientific scientific community, in
this case, actually provide a couple of,
ideas and techniques we can use to mitigate,
this kind of, you know, declining performance of
qubit of temperature.
So that's one one of the aspects a
key very important aspect. Keep increasing the temperature
of the qubit, but at the same time,
make sure that the quality of the qubit,
the coherence time is still very good.
Maybe also to note,
scaling up the number of cubits as well.
Even if with mature technologies, like, if you
look at the current state of the art,
we are talking about 100, maybe few 100
of cubits.
With quantum dots, again, as I as I
mentioned, so we we basically leverage. We use
semiconductor technologies. With quantum dots, potentially, we can
build many many quantum dots on the same
chip, on the same type. They are very
small. They can, again, utilize the same technology
as classical transistors.
However, we still need to push boundaries. We
still need to improve the process. So it
means
better quality of, silicon, better quality of materials,
improving quality of deposition of metals. So, actually,
again, process steps must be much, much fresher,
much cleaner, and so on.
And,
so, basically, yes, quality control material control quality
control is is going to be very important.
On the good side,
we can see that a number of foundries,
thinking of this, and there is quite a
lot of momentum, quite a lot of lot
of effort to bring the existence in the
conductor processes to this quantum standard.
So we can see that
there are really significant efforts, okay, to decrease
the dimensions of the metal gates, to improve
the, quantity of materials. So that's also work,
in progress also on a foundry side as
well.
I see. And and when you when you
deal with people in the in the semiconductor
industry, do you find that they're very keen
on
on quantum
computing? That they're interested in working with with
your company and and I suppose other companies
to to create chips and and drive the
technology?
Yes. I would say there is a lot
of interest. At least a lot of interest.
Yes. Because,
we hear about quantum applications. We hear how
we can unlock the potential of quantum confusion,
like, classes of different applications,
particularly compatible, again, with quantum algorithms. And so
there's at least interest. Okay? So what can
we do about,
how how we can improve it? And, like,
when we talk about semiconductor
qubits or quantum dot qubits, again, this is
the main of, semiconductor
industry, right, where, again, the progress decades of
progress.
So and in some of the some cases,
yes, there is a significant support, significant support.
Okay? So how can we improve? Like, how
can we improve the process? Can you provide
us feedback? Can you, I mean, like, can
you share? Can you, help us to understand
the performance of, like, our process? Like,
quite often, we would have a collaboration or
kind of iteration process where we would discuss,
review feedback, and change maybe some of the
design design to keep based, based on the
discussion.
So in my opinion, there is a lot
of interest and support from foundries,
to make sure that quantum semiconductor process happen.
I see. And and you've already touched on
on this idea of quantum error correction.
And and I think that your systems offer
integrated
quantum error correction.
Why is error correction
necessary?
And and how is it done?
I okay. So maybe I would say that
it's
fundamentally virtually impossible
to make a ideal physical Qubash.
So it's impossible to isolate a keyboard from
the environment. And
when we operation the qubit, there is always
some
fundamental underlying interactions going on. So
it's manifested by a qubit losing the quantum
information to the environment, like one of the
typical channels. Okay? It's like, incoherent noises. Like,
basically, qubit losing this quantum information. And,
we could characterize this loss or kind of
this nonideality
by different metrics.
So I said few times coherence time. That's
one of the indications. So it's kind of
a time where,
kind of, qubit
keeps the enough kind of amount of quantum
information
isolated from the environment. Like so it's a
little bit awkward, but, like, it's kind of
like an indication.
In all these metrics, you can measure. You
can, like, really see how much of nonideality
is going on there with qubits.
And even the best qubits,
in other platforms, we are still not ideal.
Their coherence time, their fidelity, their kind of
performance magic are still not, like, not, like,
100%, like, ideal. So
physical qubits are noisy. They experience this interaction,
so it's going to happen. Like, we need
to think about, like, a form of error
correction, a form of mitigation.
But if you think and, again, I will
oversimplify. But if you think what's what's the
idea of error correction, it means dash
we will try to store quantum information not
just in 1 qubit, but, like, in the
multiple qubits.
So it means we are going to distribute
this information across maybe, like, maybe 2, maybe
3, maybe 1,000 qubits. So it depends again
on the type of error code.
And then it means we need to be
able to reset, entangle,
measure,
selected qubits, not all, but selected qubits in
this column. Array. And it means we also
must make a decision
if, an error is happening there. So and
you need to do it, like, in real
life or in kind of in real time
while qubits are still coherent. And that's a
lot of operations,
involved in the game, resetting qubits, measuring qubits,
and so on. All of that takes time
in the qubit also decoherence. The qubit also
is not ideal for infinite amount of time.
So and you can, again, understand. So it's
a real challenge to build such a system
that works fast, that makes a decision, and
again, in real time, and so on. And
in order to do that, that's why you
need to, again, have all those components closer
to qubits on the same dice so you
can exchange the separation,
information,
faster case, so you can make decisions and
so on. But then I was that's why
I was talking about the creation, how important
it is, because
dash must be a chip that must be
very close to cubits. So you can really,
really, facilitate. You can really, like, apply this
error correction in real time when the cubits
dash, you know, kind of will decay in
some amount of time.
Elena, you were talking about temperatures
and, you know, the fact that you you
have to run your your the the quantum
side of your of your chips at at
cryogenic
temperatures and the importance of being able to,
you know, maybe do that at a slightly
higher temperature.
Do you think that someday it might be
possible to to run,
quantum dot cubits at room temperature?
Or will they always have to be cooled
down
using cryogenics?
Yeah. Okay. Yes. Great.
Yeah. It's a great question. I
I I think it will be a dream
for the entire quantum engineering community to see
quantum confusion, quantum phenomenon operation at the room
temperature.
However,
I think that my answer for the moment,
okay, short term, maybe even mid term, medium
term will be probably no.
I think we will have to discover a
completely new material or a completely new phenomenon.
Okay? So to facilitate a quantum confusion at
room temperature.
And if again, I can I maybe, like,
expand a little bit, but I think so?
It's if you think about
actual
properties of different materials, in particular semiconductor materials
at room temperature, at cryogenic temperatures, which is
again millikelvin or, like, 1 kelvin range,
the the properties are quite different.
So our normal temperature, room temperature, will generate
a lot of thermal fluctuations, and thermal fluctuations
leads to thermally generated electrons and holes. So,
basically, typical material is flooded with charge carriers.
There are so many elections and holes, even
in, like, dielectric materials.
And we are talking about numbers such as
10 to the 10 charge carriers per cubic
centimeter,
and even weighing metals. And remember how we
were saying that, in order to build a
quantum dot qubit, like a semiconductor spin qubit,
you have this potential well, and you trap
an election and you manipulate a spin there.
So but you trap one election.
You cannot be able to do it efficiently
in the material with, like, a large, large
number of charge carriers. And that's a very,
again, very typical behavior for semiconductor and dielectric
materials at room temperature. So I think in
this particular case, we'll have to hope, okay,
Dash, we might discover some new process, some
new materials, some new phenomenon because you never
know what happens. Science and engineering keep delivering
kind of, you know, new discoveries. So it
might happen and not going to reverse out.
However, I think, again, like, you know, maybe
not not in the very, very near future.
I don't think so.
But maybe if I can comment on this
because I think it's important.
If we can keep a strand, if we
can actually can keep
quantum dots
or quantum dot cubit like a or spin
cubit, operation at 1 Kelvin, that will be
incredible. I think that will be really, really
huge progress
because
I know it sounds like a very low
temperature, but it's actually they are quite efficient
systems to cool down to 1 Kelvin. So
there are now very compact machines. You can
it's they they don't do not consume that
much power. So it's, and, like, they're actually
like a desktop or maybe, like, a server
size.
So, it's not that because Flash is used
to be. So
if if if you can catch a cube
at parking at, like, even 1 Kelvin, that's
going to be already, like, a hot kind
of, you know, temperature cube or kind of,
you know, it's it's going to be a
it's going to be an incredible progress. Yeah.
Yeah. Well, actually, that's a good point, Elena,
because, you know, at a bit outside of
quantum computing, you know, for example, at the
Large Hadron Collider,
huge systems there are maintained at cryogenic temperatures.
So it's not really
that that much of a
technological challenge, is it, to to
to cool things down?
And and finally, Elena, I just wanted to
ask you what equal one is working on
today. Do you do you have a functional
and practical quantum computer?
Or, are there further modifications,
that you have to make to your system
and and challenges that must be overcome
before you reach that goal?
We work right now on a few variants
of, quantum dot cubits or spin cubits
because, again, even like we say at the
same time, there's actually multiple different variants there.
Each, will have its own metric. And, again,
maybe compatible with some particular, like, you know,
type of electronics. So we we we investigate
this.
But I think most importantly, from the point
of your quantum hardware, we work on a
6 quantum dot or 6 qubit processor at
the moment we test this device.
And we test, integrated controller to control the
6 qubits.
So that's a work in progress.
In addition to DASH, there is a design,
development of a cryo mechanical system to maintain
the temperature for this, 6 qubit processor.
This, I think, I mean, looking at one
of the most important thing because it's the
actual hard quantum hardware.
But generally speaking,
if you've kind of also if I would
think about, like, a range of engineering and
scientific problems to help, okay, to support this.
Okay? So I I say I was mentioning.
So,
we we are we are working on a
new type of sensors which will be very
fast for error correction. So we'll be able
to detect the spin state within order of
magnitude of a microsecond.
That's, kind of our goal.
So, we optimize quantum dots. So we see,
I'm looking at what's the best dimensions,
kind of, you know, what's the best materials
as well. And we look at the specific
systems to deliver microwave pulses to control spin.
And,
I at the beginning, I was mentioning, so
the team is actually very, very broad. So
we have, like, different skills. We also have
a team working on quantum algorithms,
and, so there is a work on
original method for error mitigation.
And, that's something like, you know, some series
of works we are going to present this
year in different workshops and conferences.
Oh, well, that's great. Thanks, Elena. Thanks for,
for talking to me about, Equal 1. And
congratulations again to you and your colleagues for
winning
the Cubic Prize.
Thank you.
Thank you for inviting me. Thank you.
Brandon Grinkmeier is a Physics PhD student in
the group of Misha Lukin
at Harvard University in the US.
The group is active in the fields of
Quantum Optics and Atomic Physics and is at
the forefront of developing
Quantum Processors that use arrays of trapped atoms
as quantum bits.
Physics World's Margaret Harris caught up with Brandon
at the Optica
Quantum
2.0
Conference,
which was held earlier this summer in Rotterdam,
the Netherlands.
As you might expect, there was a buzz
of excitement at the conference, which you will
hear in the background of their conversation.
So, Brandon, what's what's it like being part
of a research group that's doing cutting edge
work in several different areas of quantum science
at once? Yeah. I guess it's really exciting
being part of the Lukin Group because there
is such like a big diversity of people
working on so many different things. So it's
really nice to be able to get like
a spectrum of people working on like quantum
sensing
as well as like quantum computing, quantum networking.
And then like, what I work on is
actually kind of at the heart of a
lot of these things, which is, like, very
nice for me to be able to have,
like, all these different communities to talk to,
but also very nice to have, like,
I don't know, a lot of expertise around.
So what what do you work on? Oh,
and then so,
like, there's different subgroups in our lab. There's
a lot of people that work on quantum
computing, quantum networking, and quantum sensing.
My project is actually taking
the quantum computing aspects and combining that with
quantum networking where we can try to have,
like, a quantum computer that can then connect
to other quantum computers in, like, a modular
fashion. So more generally speaking, like, modular quantum
computing. So in particular, we trap single atoms
in optical tweezers and manipulate them like cubits.
And then we couple them to optical cavities,
which gives us a photonic interface that we
can then use to distribute this entanglement to
other quantum computers,
essentially. And why is that gonna be necessary?
Yeah. So I guess
at some point, people believe that there will
be a limit to how many cubits you
can have in a single quantum computer. And
at that point, in order to scale up
the number of quantum
or and cubits in your processor, you'll need
to find some way of
distributing the entanglement or doing this, like, modular
quantum computing.
So when you're you're doing this this sort
of, you know, sort of putting a single
atom is a single atom into a into
a cavity Yeah. And then coupling how does
that work? Tell us a bit more about
that. Yeah. So I guess, our platform, we've
explored a few different types of cavities, actually.
So early on in my PhD, we were
working with these, like, nanophotonic
cavities, which is something very special. It's something
that, like, has really only been, like, achieved
well
in the in the Luken group early on.
So, like, this was work done maybe, like,
a decade ago now where people actually managed
to take a single atom and trap it
and then move it onto,
like, a nice,
silicon nitride nanophotonic
device and couple to the photonic mode of
that device
in a way where you can now have
coherent coupling between an individual photon and this
individual atom.
The other platforms that I've kind of worked
on throughout my PhD and kind of, like,
developed
throughout the last few years has been, coupling
to optical fiber cavities. So this is a
different platform.
It's,
it's more like a
traditional
cavity where you have,
free space mode formed by 2,
curved mirrors and you can put an atom
inside of that. The way that we do
this that kind of makes these platforms
pretty compelling in terms of integration with,
quantum computers is
we can just trap the atoms right above
the cavity or nearby with the nanophotonic
device or the fiber cavity device and then
move them in. So we do this, like,
coherent transport process that's also done in the
quantum computing.
So So this may be a slight unfair
question, but I know there are also people
working on doing quantum computing with photons, which
I guess sort of skips Yeah. The the
atomic step from there and just starts natively
with with photons.
Yeah. Yeah. What are the advantages of adding
this extra layer complexity effectively and starting to
have atom cubits that communicate with photons? Yeah.
I guess photons are
kind of necessarily lossy by having, like, a
matter interface. You're able to store, like, the
the cubit state on something that you can
kind of keep around. So
the the kind of architectures that we think
about are doing all of our quantum computation
on matter cubits and just using the photonic
cubits as kind of a bus to distribute
the entanglement between nodes. Because as, like, classical
communication has taught us, like, communication over fiber
is one of the, like, best ways of
doing long distance communication.
I guess the other kind of interesting thing
about our platform is there are also applications
where we can couple a matter cubit to
this photonic mode and generate interesting non classical
states of light as well, which is something
that, like, in our field
with of neutral atoms, we have been very
good at as well, and it's something we're
also interested in pursuing.
Interesting to me, like, how all these different
technologies fit together because it's good that you
need to have all the pieces in place
before you can actually build a quantum computer
that communicates with other quantum computers
and that
potentially has error correction, you know. What are
the the really big challenges in in that
space that you you're focused on? Mhmm.
I guess
so historically,
people have done, like, quantum computing with neutral
atoms.
And as, like, recent results have shown, it's
it's a very promising platform. And people have
also separately done, quantum networking with neutral atoms.
And that's also been, like, very promising. I
think some of these, like, neutral atom experiments
are also, like, kind of some of the
best in the world as well. And so
trying to put those together
ends up being somewhat of a difficult challenge.
It's something that we have, studied quite a
bit as well. So one issue is that,
when you're you're using these neutral atom computers,
the way that you perform gates is by
exciting your atom to a Rydberg state. And
these So what's what's I'll just pause you
there. What's a Rydberg state? Yeah. So
a Rydberg atom is a highly excited atom
where you excite the electron to, like, some
high,
principle quantum number state. And essentially that takes
your electron far away from the nucleus and
forms like a a very large dipole in
kind of a classical picture. And that large
dipole gives you strong interactions
with other dipoles, which is great for doing
gates, but also bad if you are near,
like, for example, a surface. And if that
surface has charges, then it causes issues with
coherence of this red burst state.
So that's one of the issues that we've
been trying to tackle, which is,
these optical cavities that we work with are
like macroscopic
devices. They're made out of dielectric and they
host charges and these charges can fluctuate which
would lead to fluctuations in the Rydberg,
coherence.
And as a result that could lower your
gate fidelities. So we did some, recent studies
where we studied how the Rydberg atom,
is influenced by a nanophotonic
device and how we can restore coherence of
that Rydberg atom by performing some special,
pulse sequences.
Then beyond that, we can,
think about things like,
tailoring
quantum gates that are now more robust to
these charge sources. And the other kinds of
architectures we think about is not performing the
gates, like, near the nanophotonic
device or near the cavity, but kind of
transporting from a logical processor into this photonic
interface and back and forth. And does that
mean physically sort of moving the atoms by
magnetic fields or something like that? How do
you do that? Oh, yeah. So the way
that we do,
kind of atom transport is we work with,
arrays of atoms trapped in optical tweezers. Each
optical tweezer
corresponds to some, tone and an acoustic optic
deflector in most cases.
So an acoustic optic deflector is a device
where you can send in a single beam
and then by just
driving tones on the
the acoustic optic device, you can create an
array of, beams. And each beam then can
be focused into an image plane to an
objective to correspond to a single trap for
a single atom. And then by changing the
frequency of that tone that you're driving the
AOD with, you can move the, the trap
in space. And so this is something that's
been, I guess
I guess, developed mostly in in our group
at Harvard,
to do atom transport
in the middle of, like, quantum circuits but
also for, like, transporting atoms into,
like,
cavities, optical cavities.
Right. Right. It's the base technology. It kinda
has different applications. Yeah. Yeah. Yeah. So I
wanna actually turn to that that, that application
you mentioned because, you know, I'm referring to
the sort of
stunning demonstration of 48 logical cubits that was
done in,
Mitchel Lukens group by some of your colleagues
earlier this year. And I think for a
while, it seemed like other technology platforms, you
know, superconducting circuits, maybe ions, to scrap ions
to some degree, had really been making all
the headlines in quantum computing.
And this result, I think, kind of surprised
some people.
You know, should they have been surprised that
that your neutrality was so so good at
doing this sort of thing?
I mean, I guess from an outsider perspective,
I think that it it would be pretty
surprising because this is, like, a goal that
many companies
were saying would happen in, like, 5 to
10 years. And it is something that, like,
everyone thinks is this, like, very far off,
development. But I think from,
like, an insider perspective seeing, like, the development
of neutral atoms over the past 5 to
10 years, you can actually kind of plot,
like, gate fidelities as a function of time
and you can then fit, like, a line
to it. And you'll see that at, like,
this point in time it was kind of
it. I mean, if you trust the linear
fit, it it crosses quite literally a threshold
where you can now,
do error correction in a way where you
can actually see an improvement. And that's kind
of what sparked
this this development. So they had a lot
of the pieces
early on,
I guess, in, like, 2022,
I think. They had this coherent transport
to do, like,
like, like, it was like a quantum processor
based on coherent transport of atoms and optical
tweezers where they could do non local,
2 cubic gates. But their gate fidelities were
still around, like, 95%,
I think. And that was that's not enough
to be able to do error correction where
you actually see a benefit. But then,
after a lot of, like, technological
development and collaboration with industry as well, they
improved their laser systems and also developed a
better understanding of how to do the, like,
do these time optimal gates, they were able
to bring down their, gate fidelities to around,
like, 99.5
or bring up their fidelities to around 99.5%.
And that does cross this threshold where error
correction will now, like, give you a benefit.
Then by combining all of these pieces, they
were able to then do this logical processor
work.
Yeah. And the the the the interplay between
technological developments and scientific ones is, I think,
particularly strong in this field. Now what what
do you think has been the biggest game
changer in in your research, technologically speaking?
So in in particular for us, we collaborate
a lot with, people in the applied physics
department actually where we we benefit a lot
from developments in photonics.
So a lot of our devices are fabricated
in the clean room and it's not really
an expertise of our group but we have
nearby groups that work on nonlinear optics
and advanced fabrication.
And I think the development of these fields
is is very important to us. And they
are like continuously, like, progressing these photonic platforms
which we can then make use of almost
immediately in our lab. And I think this
connection between applied physics and physics in our
group is is very special. Like the so
many people are familiar with the Adamurie experiment
but there's the silicon vacancies experiment, which is
one of I guess recently
they've demonstrated this Metropolitan,
Quantum Network in Boston, which is, like, an
amazing result. And it's really the
kind of the collaboration
between the, like, Marco Longhard's group where they
developed,
very particular type of fabrication
and the expertise of the Lukin Group and
and Quantum Networking that made these things happen.
And it it's these connections that I think
are extremely important.
K.
And, you know, what are the next steps
for for you and your research? What's what's
coming up next for you? Give us a
preview. Yeah. So I guess
it's in my opinion, it's a very exciting
time. So I've been working on this one,
like, this platform coupling atoms to this new
type of optical cavity, which is also being
developed in collaboration with the LUNCAR Group as
well as Keule Yang's group and, the applied
physics department.
And we're just starting to,
I guess, see results from it and know
that we can make it work. Now it's
just about implementing it at a larger scale.
So we wanna work on modular quantum computing,
and in order to do that we need
multiple
devices. So we've started building a second experiment,
and we're starting to scale up the main
experiment to act more like a quantum computer.
And then I think we'll be able to
demonstrate some of these, like, modular quantum computing
applications
in the near term. And I think there's
also other very interesting things that we can
do just on,
like, just on the scientific side of,
like, more interesting, more novel interactions that you
can do between photons and atoms in a
cavity.
Such as?
I I guess it it it would get
pretty technical but Okay. So so I guess,
like, we're so we're about to publish this,
work where we're able to use,
the
the strong coupling between the atoms and the
cavity to do kind of long range,
entanglement generation, which is I think it can
be potentially useful to supplement the quantum computer.
But it's also just an interesting avenue on
its own because cavity interactions
are very special. They can generate, like, squeeze
states and I think that a lot of
our work can kind of,
advance that field as well in a way
where we can produce maybe better and, like,
better squeezing
and,
have applications
more in in that domain. So squeeze state,
just remind the listener's names. Yeah. So,
I guess one of the biggest applications for
optical cavities and neutral atoms in our field
is you would place an ensemble of atoms
inside an optical cavity. And then by performing,
like, non destructive
quantum measurements on it, you can take the,
like the,
like the atom number distribution
and essentially squeeze it in,
phase space, which which gives you more precision
for,
any,
measurement of phase that you would do. So
for example, if you were to take
an ensemble of atoms and perform clock interrogation
on it, you can get some,
limit on your sensitivity which is given by,
like, the the projection noise limit. But if
you were to use a squeeze state, you
could go below that and get, quantum projection
noise limited.
So that's just an example. Squeezing generally is
you you sort of, reduce the uncertainty Yeah.
One variable Exactly. At the expense of another
variable that you don't care as much about.
Yeah. Yeah. Yeah.
Yeah. Okay. And what's next for you personally?
You must be coming toward the end of
your PhD or or not yet? Yeah. Sticking
around for a while? Yeah. So I'm a
5th year graduate student. I guess I'll be
starting my 6th year. So I am starting
to think about what to do next. I
think that these, these platforms that we've been
developing are very exciting and I would like
to
see them,
like, make make some things happen. So I
am
thinking
about
what to do next but not not exactly
sure. Yeah. Brandon Brickmars, thank you very much.
Yeah. Thank you.
That was Harvard University's
Brandon Grinkmeier
in conversation with Margaret Harris.
Margaret has written about the Optica Quantum 2
Point Naught Conference
on the Physics World website.
Under the headline,
Bringing the Second Quantum Revolution to the Rest
of the World,
Margaret looks at how physicists in low and
middle income countries
are trying to ensure that their regions develop
and benefit from quantum science and technology.
Margaret also looks at the current trend towards
fault tolerant
quantum computing
under the headline,
how to get the errors out of quantum
computing.
You can find both articles
in the blog section of our website.
CERN is one of Europe's premier research facilities.
And this year, the lab is celebrating its
70th anniversary.
In the latest episode of the physics world
Stories podcast,
2 former
public relations
gurus at CERN, James Gillies and Achintya Rao,
look back on some of the highlights of
their careers.
These include welcoming Hollywood royalty to the lab
for the launch of the film Angels and
Demons
and the announcement of the discovery of the
Higgs Boson
at the lab.
That episode is hosted by Andrew Glester
and is called CERN at 70.
How the Higgs Hunt
Elevated Particle Physics
to Hollywood Status.
You can find it on the Physics World
website
or at your favorite podcast provider.
And the CERN celebrations
continue here at Physics World.
On Thursday,
26th September, we present
the future of particle physics.
This is a Physics World live event produced
in partnership with the journal
Reports on Progress in Physics.
The live panel discussion
will feature Tara Shears of the University of
Liverpool,
Phil Burrows
at the University of Oxford,
and Talika Bose of the University of Wisconsin,
Madison.
They will explore what the future holds for
high energy physics
and where the next particle collider
should be built.
You can register now for this free event
on the physics world website.
Just click on the physics world live tab
at the top right of the homepage.
I'm afraid that's all the time we have
for this week's podcast.
Thanks to Brandon Grinkmeyer,
Elena Blakina,
and Margaret Harris for joining me today.
And a special thanks to our producer, Fred
Iles.
We'll be back again next week.
See you then.