Transcript | A UK-Based Quantum Computer via Amazon

Quantum computing via cloud access feels global, but there are reasons to have these machines located in a particular region. Oxford Quantum Circuits released a quantum computer named Lucy that not only helps customers with regulatory concerns but also brings an exciting new type of transmon technology to the industry.

Find out more about the Coaxmon approach to building QPUs in this episode of The Post-Quantum World. I’m your host, Konstantinos Karagiannis. I lead Quantum Computing Services at Protiviti, where we’re helping companies prepare for the benefits and threats of this exploding field. I hope you’ll join each episode as we explore the technology and business impacts of this post-quantum era.

Our guest today is chief technology officer at Oxford Quantum Circuits, Simon Phillips. Welcome to the show.

Thanks. It’s great to be here.

I was looking at your background, and it seems like an interesting path you took to Quantum, so if you want to spend a moment filling us in on that.

Yes. I’m probably one of the few CTOs in the quantum computing space who spent most of my life making video games, actually. Twenty-five to 27 years ago — I started losing count — I signed up with a video games program, and it is relevant. I hope the relevancy will come through. I started as a machine code programmer, making MIDI games and writing 68K and things like that.

Over time, I got into the technology side of video games and then running businesses and things like that and seeing a lot of different emerging technologies coming through. And it grew into one of the world’s largest markets, one of the largest industries, and I learned a lot of different things over time.

I met [OQC CEO Ilana Wisby] five or six years ago, just before she was asked to come to work as CEO. We got talking about what we’re up to and making video games, and at one point, I did ask if she was going to come and work for me, and then the tables turned. I was speaking to her when she started with OQC, and I had this intro about video games where I genuinely thought we could change the world with video games. After a fun conversation with Ilana about quantum computing, she convinced me that I should come and join her over here.

For me, there are so many similarities with what we do at OQC in terms of quantum computing in general. It’s such an emerging market, so there are things that we’re doing that just never existed before. There are business models that have never existed before. There’s technology that has such an infancy that we just know is going to scale and become useful. All of those things like feel like things I’ve done in video games in the past.

So, when 3D games first came out and someone dropped a PlayStation on my desk when I was a teenager and we made 3D games when free-to-play gaming came out, and it felt like madness at the time — you’d spend $10 million making a video game and then give it away for free — defining those business models and how you deliver that technology to consumers is what we’re seeing now in quantum computing. But, yes, I don’t have a background in physics. I’m fortunate enough to have an amazing technical team here at OQC — we have a number of quantum leaders in various fields. There are connections with Peter Lee of Oxford University and his league clubs there as well. So, you’ve got a lot of the technical science bases covered, and my job is to build this with a strategy that’s old enough to deliver this technology to our consumers, and that’s exciting for me.

Yes. Emerging tech experience is very important in an emerging field like this one.

Yes. Working with video games has taught me to be quite brave, and one thing we say a lot at OQC is, we’ve got to stop being British about this. We’ve got to be bold, we’ve got to be ambitious. We’ve got to be realistic, of course, but, yes, be brave a lot of the time as well.

I like that — “Stop being British.” I never heard that expression. That’s funny.

In the early days, I don’t know if you remember that with the first Qiskit tutorials, some of them were games.

That’s right. Yes.

Those must’ve looked so primitive to you.

Yes. Now, it’s easy enough to look at an entire circuit in assembly language and understand it because in a handful of years, this is going to be unrecognizable.

Yes. The depth is going to be wild as the machines are able to handle these circuits. Tell us a little bit about Oxford Quantum Circuits.

What an exciting place it is to be at the moment. We’re fortunate, and we’ve got our core technology. We spun out from the University of Oxford in 2017 from a core piece of technology invented by Dr. Peter Lee, which is the Coaxmon. This is a 3D integrated solution for transmon superconducting technology that takes it back to first principles about, what if we could do away with all the things that are fundamentally limiting coherence and noise and crosstalk within quantum circuits? How would we redesign it if we start it from scratch?

Peter Lee came out with a Coaxmon. So, whatever that is now — five years ago — it was a patent, a piece of paper and some theoretical ideas and some things from the university. We spent the first three or four years bringing that technology out of the university and learning how we can recreate it and how we can start scaling it and how we can engineer it to be what we want to see for conducting circuits to be — this low-crosstalk, high-coherence platform for scaling quantum computers.

We were doing well spinning that out at the university. Then COVID-19 came along and forced us to spin out of the university, and suddenly we didn’t have access to facilities and things like that. We very rapidly built the team up so we could start fabricating our own Coaxmon-style devices using university recipes and things but without the reliance of the university, which is important when we started growing the company to be its own commercial entity. We got the basis of it, and we were able to very quickly demonstrate that not only could we create a multiple-qubit process, but it’s also an actual process, and so we’re talking about fully connected qubits and we could demonstrate that.

Then, we had what were side projects and are now massive technical pillars of the company. We designed and built all of our control hardware from scratch as well, which felt crazy when we started it. Now, there are a lot of technical advantages to doing that — similarly, with our own compilers, optimizers, cloud infrastructure and all the things that go towards that in 2022. It was 2021 when we launched Sophia, which was our four-qubit process, and it was our full end-to-end stack. That was a third-party customer delivering a piece of code over our cloud infrastructure to use every part of OQC’s technology to deliver results in the back end. That was a thrilling time, and we did all of that within four years.

That was less than a year ago, and since then, we’ve scaled the process up to eight fully connected high-currency qubits, and launched on AWS as well. That rate of progress has been quite staggering, and then it’s all down to this core that we’ve got around the Coaxmon that allows us to scale without introducing more crosstalk and things like that today. Yes, it’s been wild.

Before we start talking about the new machine, a little bit about the Coaxmon and the processor would be in order here. If you look back at IBM’s first transmon processor, it’s flat, and it’s just little snaking leads, and you have this five qubits, and you had to try and get them to talk to each other. How would that compare if the audience wanted to visualize a Coaxmon processor? If you have eight qubits, how are they arrayed?

You’ve got the same key components — your qubit, your resonator — and you read out lines and all that sort of thing, but we arrange them in complete 3D, so this is the core pattern. Rather than having everything trying to fit in a 2D space and then you’re trying to basically maximize that 2D space out, so you’re keeping your eyes away from your qubits and you’re trying to control the environment, we bring it all in 3D. It looks simple, and I hate to call it simple to the entire fabrication team, because there’s a lot of hard skill that goes into it. We do two-sided fabrications — we have a qubit on one side, and then we have a resonator on the other side, and then control lines coming from the top and the bottom, so the whole thing is stacked in 3D.

The real magic is, we never galvanically bond to the chip itself. We use capacitive coupling to go through the qubit and resonator. What that means is, everything is limited to this plane here, so the crosstalk is minimized. The surface of the chip itself is so simple. You’ve just got a qubit on the top and a resonator on the bottom, so we can build out complicated arrays of qubits and different connectivity patterns without worrying about where all the control wires are going and things like that. It’s a clean, neat, very simple solution to a quite complicated problem.

You can visualize it almost like each qubit is an invisible cylinder with a qubit in the center and the controls on top or bottom. Then, you can have as many of these invisible cylinders close by as you can. So, that’s where the 3D comes in, in the control piece. It’s not like qubits are floating higher and lower.

The great thing is, because it’s all capacitive coupling and there’s no bonding —there are so many different technological niceties. You could call them advantages, but we can create an environment where we can open up our sample holders, we can pull the wires away and we can change the chip because we don’t bond to it. So, when we’re in R&D, we could throw a quick R&D without having to use bonds or flip chips or all those kinds of complicated things that would go into a normal 2D architecture to around wiring issues. Yes, it’s pure and simple. It’s quite cool.

This eight-qubit processor — would you consider this a unit going forward, like a computing unit? With IBM, their newest processor, it’s 127 qubits, and how are they going to meet the road map? Well, they’re going to put four of those down, and then they’re going to put down 10 of those. Is it going to be like that, where you’re going to have that one little chunk of eight, or are you still completely flexible?

Yes. There’s a number of bits of technology there. Again, because of the capacitive coupling, we were able to do neat chip-to-chip modularity. We can capacitively couple through a qubit and a resonator. We could put another one on top and two qubits stacked on top of each other, so, when it comes to building modularity, it’s — again, nothing’s straightforward, but in the grand scheme of things, it’s relatively straightforward for us to build out this modular unit. But we’re nowhere near the limits that we have to do that kind of thing yet. We can go much bigger before we need to module it.

Bear in mind that as we scale our process in 3D, it’s getting linearly larger. So, every time we have to bank qubits, they’re not quite in a grid, but if you imagine a grid getting bigger, we could add n number of qubits. We’re just getting slightly larger. We’re not getting exponentially larger like a 2D setup would be with its wiring fanning out, so we can go large before we need to go modular, which is quite smart. Then, we get into more engineering challenges than we do QPU challenges before we have to go the chip, but the Coaxmon allows us to do some neat stacking of chips and tiling of chips, so we’re excited about when we get into these large-scale systems.

So, you’re still a while away from having to do the equivalent of multicore.

There are good experiments we can do with it. We can even put connectivity patterns on layers. So, we can have a pure array of qubits and then we can have different connectivity patterns that are laid on top if you want to do very specific experiments, or something like that.

I’m assuming there are more benefits than just space saving. Have you tried to measure these eight qubits against the competition? Do you use benchmarks — something from Super.tech, like Supermark? Or do you experiment with quantum volume and that kind of thing?

Yes. Quantum volume is an important metric for us. We know inherently in the design, we have leading low crosstalk between the qubits, which is also important as we start scaling, and we don’t want to start compounding errors. We have naturally high coherence based on the simple design and the fabrication design as well. We’re seeing some experimental QPUs and some work that’s been done with the University of Oxford that are getting high, like T1 and T2, which is exciting. By the time we distill the whole process down, and we try and make a useable eight-qubit process, and not all of those premises filter down, but we’re excited about the potential of it.

Yes, we use quantum volume as a basic benchmark, if you like, and we’re pretty pleased with where we are, considering the life cycle of our processes. I know when we launched on AWS, there was an independent paper launched that had some basic benchmarking down. We were relatively high up there compared to some people who make superconducting circuits that are much more mature than ours. But, yes, we’re pleased with the performance, and it’s getting stronger all the time.

Are you comfortable sharing what the quantum volume is for Lucy?

Yes. We’re still in the 22, 23, but we’re in a world where we’re going from 22 to 23 just based on calibrations. There are no specific hardware changes — again, bear in mind we’ve got the full stacks, and we’ve come from our software-era compilers, shaping pulses or tweaking the control hardware. We’re still able to find these real low-hanging fruit, and we often joke about it — I think it’s the wrong word, but there’s so many areas to attack. You’ve got to pick the right ones for the road maps — “All right, let’s progress down this road” — but we’re fairly competent that we’ll continue to make quantum volume gains within our eight-qubit process.

As we move on to our larger-scale processes, we’ll get the same or better volume as we go forward, because we never change the architecture. It’s the same unit cells, just larger and larger, so we’re not dealing with complete new architectures like you might find in a 127-qubit process, for example, where there are extra challenges that come in there. We’re seeing the performance gains as we add more qubits.

Do you have a sense yet of what your road map might be for a couple of years? Do you see it, like, “This year, we just add more of these imaginary cylinders?” — I just want the audience to understand — and then, would you then say next year, “Now, we’re going to start stacking more on top” — like you said, the whole other layer? Did you give thought to that?

Yes, definitely. We have so many different variations of road maps just in terms of from a pure content-volume point of view. We’ve got a good idea of where want to get to and qubit count where we want get to, and then, ultimately, what that’s going to distill down to is, yes, quantum volume and error rates and things like that we want to tick off.

Really, the one that reinforces that as well is the infrastructure and commercial road map — we want to tie these things together. So, what our aim is, as the technology gets better, the ability of our customers, the learning journey that customers might be on, is getting better and infrastructure is getting better. So, all those three things need to come together in a number of years’ time to make sure that people are learning how to use quantum computers today at the eight-qubit level.

I want to go back to talking about programming-assembly language and understand the fundamentals before it gets too complicated. If you can start programming an eight-qubit process today with a modest quantum volume, as that grows, you’ve got to grow into it in terms of the journey, but at some point, when you’re ready, you want to have much higher quantum volumes and high circuit techs and things like that, and the infrastructure to use it as well. By infrastructure, I mean the feature sets, moving to OpenQASM 3 or whatever the customer journey is as well. We’ve got a lot of different things to squeeze out the stack, and we remind ourselves a lot that we’re a quantum computing–as–a–service company, not a qubit-processing manufacturing company or a hardware — we do everything to make quantum computing as a service, so every part of that stack is just as important as the rest.

I’d love to hear a little more about Lucy. It launched on AWS in the UK. Is this the only way to access it right now?

No. We have our own private code access as well — always, part of our road map was public access via AWS. We don’t need to have customer interaction. You can just log right on — you can experiment and start using the process, which is fantastic. We also have private cloud access. We have a cloud API that we can work directly with customers on, and we’re seeing a lot of attraction there as we take on the role of an on-ramp, learning how to write quantum algorithms or learning how to use quantum computing. It’s more about the relationship with the customer, and it’s going, “How do I start thinking about quantum algorithms away from task cloud algorithms,” or “What sort of problem should I be looking at?”

We build our cloud infrastructure around our private access, so I could give you an API key now and you can log on, and we could do a deal between us for accessing and consultancy work with our engineers. You work with our BD team and things like that to help identify the sorts of things that you should be looking at as a business preparing to be quantum ready.

So, there’s a way to select this soon, as a back-end target on PennyLane?

Yes. Again, we want to be customer-led in those integrations. There are so many core ways we could allow access, but if we can see a need for our customers — say, “I should like to access your computer like this” — we build out those kinds of integrations. But, again, the real advantage for us is, because we’ve got the whole stack, we can choose at what level you interact with the computer, which is pretty cool.

I noticed in the setup with AWS U.K., it’s very region-based, right? So, you have hours of the day that it’s accessible to that. Is it given priority for AWS for those hours — those U.K. business hours. For example, if you had a U.S. customer, would they then be better off doing it at a different time?

It’s a bit of a bugbear with windows and queues and things like this. We have a clear vision for quantum computing in the future where it should just be seamless to the user — almost to the point where you don’t care that it’s a quantum computer; you just want to solve the problem. You don’t care where it’s located. You don’t care what priority you’ve got. It just works. That’s the long-term goal — to move away from windows and queues and prioritization.

Today, we offer a number of hours to our AWS customers on the system every day, and if that is completely filled up, you sit in a queue, and when the window opens, you go again, and it cycles like that. But we want to move away from that model long-term and find a way that we can just have full accessibility. That comes with its challenges — there are not that many QPUs. We’re fortunate enough we have several live QPUs, but we’re not in a world where we’ve got thousands of QPUs online like you would have a CPU or a GPU, but that’s the way it’s going.

But, yes, today, there’s a window through AWS. If you’re a private customer, you can either do windows or deprioritized time. You might not care to have two or three hours of compute time. You might just want to run what you want to run when you want to run it. So, we’ll be able to set up windows like that, but, yes, today, it’s quite rigidly based on time zones and windows, but we want to move away from that.

Are there other reasons why it’s important to have it available in the U.K. to people in the U.K.?

Yes, massively at the moment. There are huge topics around, like, data sovereignty and data security, and even down to things like the GDPR and things like that. So, a lot of people we talk to, any data can’t cross borders, so it’s important to know where the computer’s located, how the data’s handled, where it’s physically stored, even to the point where we might go over a public cloud, but people want to know exactly where their data goes — full traceability. There’s a real reason for those regionalizations. That’s going to change a little bit over time, but by and large, people still want to know what regulations their data’s bound by when it’s processed and stored. From that point of view, the region is important.

It also makes me wonder if there’s somewhat of a misunderstanding about how quantum computers work when people worry about that. Like, what gets sent to a quantum computer? It’s so meaningless. It’s not human-readable or human-useable in any way, shape or form.

It is pretty bonks, but it’s usually one of the first things that people might ask: Where is the data stored? Where is being processed? Can we come and poke it? Does it exist where you say it does?

You’re not putting in someone’s Social Security number or something in the quantum computer. It wouldn’t know what to do with it.

Absolutely not.

In some ways, it’s good practice to make sure this infrastructure is in at this early stage, but if we’re being realistic about these sorts of things that you can run on a quantum computer nowadays compared to in three or four years’ time, yes, it’s good practice to get this stuff in place now.

If you would imagine Lucy, would you say that, like IonQ, Quantinuum, they do trapped-ion, and that’s fewer qubits, but they’re touting super high fidelity and quality and all that — connectability, gateability — and then you’ve got IBM with 127, but the quantum volume’s low, and good luck getting all those qubits to talk to each other right now. It’s just not going to happen. How would you visualize Lucy among those two extremes? How does she fit in?

The superconducting circuits, the first thing we’ve got is the engineerability, when we talk about the types of connectivity we can build in or the types of the IP we can generate. We spoke briefly about flipping connectivity patterns or changing things depending on algorithms. The big differentiator for us is superconducting circuits — again, back to the Coaxmon, we can simulate, and we know from demonstrations that we can achieve high currents and low crosstalk, which is important.

So, as we start moving into the real high fidelities and trying to move from what we’re calling noisy and somewhat fault-tolerant, we know we’ve got a good base to start with in terms of having the pros of the engineerability of superconducting circuits right up into getting into these super-low error rates and, yes, some other cool things with the simplicity of the top-surface fabrication, when we start talking about building in error-correction schemes and things like that. Obviously, we’re pointing to superconducting circuits. We think we’ve got a number of long-term advantages which some of the other technologies have today. We remain positive about where Lucy’s going to go. I don’t know if there’s going to be siblings or children, whatever we’re going to be.

But it’s so nice to have a simple core technology where we can see the engineerability and things we might want to put on one of our chips. We know traditionally, it will be quite hard with a standard superconducting transmon approach, because there’s a lot of complications.

So, trying to visualize those focuses, how would you say the pricing per shot compares for Lucy, let’s say to IonQ or something like that?

I don’t think price is a barrier at the moment, or I definitely don’t think price should be a barrier. We want to grow the ecosystem. Part of what we want to do is put quantum computing in the hands of people so you can start experimenting and start growing the knowledge base within what ultimately will be customers — these multinational companies with huge data requirements. We don’t want to block anyone out in price at the moment.

We’re on a big R&D stream anyway, so it’s not like we have a business model that says, “We’re going to be profitable within a year.” It’s just not going to happen at the moment. There’s not enough per shot demand to do that today, but what we want to make sure we’re doing is giving a fair value and placing Lucy in the marketplace compared to other technologies where we think it should be.

That’s our main thing at the moment, and this seems to work. Ask me again in a year, and I’ll have a lot more data. It’s changing a lot — going back to emerging business model thing that we saw in video games, which is changing quite rapidly as demand shifting from maybe just academics and experiments into actually having businesses starting to push for business value and things like that. It’s maturing quite quickly but, yes, I don’t think there’s a lot of science in this area.

Yes. The one big thing I’d like to see is every company having a calculator, because people get nervous. I’ve said it a few times on this show. When we’re getting ready to run some real machines, it’s like, is it going to be $20? $1,000? Sometimes, you’re not just sure it’s going to happen.

This is one of the motives behind the private cloud offering — we can sit down and set expectations to go, “We’re going to give you x amount of compute time. Don’t worry about the cost. We’ll benchmark while we start benchmarking what you might have to spend to do X, Y and Z on the computer,” or something like that, so, yes, that’s partly the driver behind the private access as we start learning what the business model should be.

One of the benefits of going through something like AWS is this ability to visualize a complete workload. You start with classical, you go to quantum, you go back to classical.

AWS did some work with hybrid jobs. I don’t know if you wanted to explain about that.

It’s pretty much moving in that direction, because ultimately, to get this vision of seamless quantum computing, you have to have fully integrated hybrid jobs, and there are some things that quantum computers just can’t do or are not very good at, so we need to make sure we’ve got the classical workload balance there. And there are a lot of complications with that.

But there’s some deeper technical design we’ve made in our process and architecture that allows Lucy to be quite well-suited for hybrid jobs. There’s still a lot of work to be done. There’s a lot of data flying around. Well, comparatively, there will be a lot of data flying around — there’s only 8 bits of data flying round at the moment — but ultimately, we need to make sure those two things synchronize. But hybrid workloads are fundamental to getting not just circuits, not just algorithms, but flat applications running on QPUs and CPUs and GPUs. All three types of technology have a place to run together to get the ultimate solution for customers.

Hybrid workloads will be ultimately driven by customer demand when they say, “This is a problem I want to solve” and then we can go, “All these are the quantum parts. These are the classical parts,” and they just want this to be seamless and work like they do anything else. When cloud computing first came into video games, again, you could just spin up all these different servers. You could spin up a GPU, spin up a CPU, and now you can spin up a QPU, and you just want those things to work seamlessly. Yes, we might be a few years away from getting this real-time, seamless, because there’s a demand element. There are a lot of CPUs in the world, and there are a lot of them idling in a lot of data centers. There are not that many QPUs sitting around idling at the moment.

Here comes the bottleneck.

The next problem is to marry out there.

Did you have to do anything special somewhere on the stack, for example, to work with AWS on hybrid? Did they need any special requirements from you?

There’s some good fortune and some foresight in design as well, but there are some special requirements to get efficient hybrid workload. Fortunately, our stack was built in a certain way that meant that they married up quite well to start with. Of course, there are some modifications that have to happen, but we were always building a stack with our eyes wide open about how this is going to work going forward, and speaking to AWS during the integration period, it was, like, “We’ve got this, you’ve got this. They almost line up perfectly.” So, yes, we’re pretty excited, and pretty timely as well, as they were launching their service around the same time that we came to AWS as well.

Yes. I thought there is some good synchronicity there. And as we’re winding down, will OQC be working on anything other than just processors in the future? Is there something you want to hint at — something listeners can be on the lookout for?

Yes. There are always things to hint at. We just remain exuberantly excited about the future. I like to say, for us, it’s not just about building the processors, and it’s not just about the whole systems. It’s about looking at it through the eyes of a future customer. By the time the customer’s ready to use a quantum computer, you want the technology to be there, you want the infrastructure to be there. We want it to be seamless. We don’t want any barriers to entry. By the time bank X, Y and Z have built their quantum information team, they’re ready to go, and they go, “Where is this quantum computer, then?” It’s right there, ready to be used at the right level. So, there are a lot of projects that go to bring that together, and one strand of that is building these high-coherence, low-error-rate QPUs, but there are a lot of things in that stack that lead this vision of seamless quantum computing in the future.

Yes. The stack is its own iceberg. People don’t realize how much more goes into these than just a processor — everything around it.

Yes. It makes me super excited when it comes to the strategy of trying to harness all of these different teams and expertise that we have here at OQC, bringing some extra partners in there that might do some things better or more economical than we can do. It’s a big volume of work, but it’s super exciting when it all comes together.

Yes. Thank you so much. I hope to have a chance to poke around with that machine a little bit in the off hours for the U.K.

Yes. You’re always welcome.

Yes. Thanks for coming.

Great. Thanks. It’s a pleasure to talk to you.

Now, it’s time for Coherence, the quantum executive summary where I take a moment to highlight some of the business impacts we discussed today in case things got too nerdy at times. Let’s recap.

Oxford Quantum Circuits, or OQC, spun off from the University of Oxford in 2017 and has been working on bringing Coaxmon technology to the world. Coaxmon is a 3D integrated solution for transmon superconducting quantum processing units, or QPUs. The hope is to achieve low-cost, scalable, stable qubits. The company builds all its own control hardware too, and the software stack.

Coaxmon processors are similar to other transmon processors in that the same support electronics for the qubit like a resonator, control lines, etc. are present. However, in traditional transmon chips, those elements have to be routed on a flat 2D plane to each of the qubits. In Coaxmon, these control elements are instead incorporated above and below the actual qubit itself. If you imagine each qubit as a cylindrical unit, you can see how it’ll be easier to fit more of them closer together by taking advantage of that three-dimensional space. Complicated arrays and patterns can be built without worrying about how to route control circuitry to the qubit itself.

OQC considers itself a quantum computing–as–a–service company, not just a qubit manufacturer. They’re concern with all layers of the stack. Their first eight-qubit machine is called Lucy. Lucy can be accessed by Amazon Braket, but OQC also has a private cloud that allows direct access. You can use an API key and select Lucy as a target. In the U.K., there are hours of availability for Lucy to minimize wait times for local companies. Customers in other regions can access as well, and the hope is to optimize queues based on time zones. Having the machine in the U.K. is important for companies concerned with the GDPR and not letting information cross borders. Even though quantum computers don’t technically access sensitive information, the concerns are still there.

Amazon has been working on hybrid jobs. Here, AWS classical hardware is used for parts of the task where it will excel while quantum computers are handed parts of the task where they will excel. Lucy is ready to work with this solution today, as OQC’s stack has already met many of Amazon’s requirements for hybrid jobs. This hybrid approach is where quantum and cloud will come together synergistically in true production use cases in the future.

That does it for this episode. Thanks to Simon Phillips for joining to discuss Oxford Quantum Circuits and their new type of quantum computer, and thank you for listening. If you enjoyed the show, please subscribe to Protiviti’s The Post-Quantum World, and leave a review to help others find us. Be sure to follow me on Twitter and Instagram @KonstantHacker. You’ll find links there to what we’re doing in Quantum Computing Services at Protiviti. You can also DM any questions or suggestions for what you like to hear on the show. For more information on our quantum services, check out Protiviti.com, or follow ProtivitiTech on Twitter and LinkedIn. Until next time, be kind, and stay quantum curious.