Andrea Tabacchini of Quantum Brilliance joins Yuval to discuss room-temperature quantum computing. Quantum Brilliance develops compact, diamond-based quantum accelerators for edge applications like robotics and satellites.
Andrea explains their nitrogen-vacancy (NV) center technology, enabling stable qubits without cryogenic cooling. With innovations in deterministic defect placement and scalable nanoelectronics, they aim to launch a commercial 60–100 qubit quantum computer by 2029. He envisions small, low-power quantum processors working alongside classical systems and sees growing investment driving practical quantum applications within five years.
Transcript
Yuval Boger: Hello Andrea. Thank you for joining me today.
Andrea Tabacchini: Hi Yuval. And thank you for the invite. This was a very good opportunity. Thank you.
Yuval: Of course. So who are you and what do you do?
Andrea: So my name is Andrea Tabacchini, I am Italian, as you can probably tell from my accent. And I work at Quantum Brilliance. I’m based in Sydney and I’ve been with Quantum Brilliance for almost two years now. Actually two years next week.
Yuval: What does Quantum Brilliance do?
Andrea: Quantum Brilliance is a quantum technology company originally founded in Australia and currently split 50/50 between Australia and Germany. Our main focus is quantum computing based on something we call integrated quantum chip, which is a small room temperature chip. I can talk more about it in a little bit. We have been born as a full stack company doing hardware and software and we envision basically a future of quantum computing everywhere. This will be tough, our uniqueness. And when I say quantum computing everywhere, I really mean everywhere beyond what people may think about quantum computing. And the reason being is that our room temperature small chip enables for a very small quantum computer with respect to most of the competition out there. And this very small quantum computer, the size of a lunchbox, maybe, the size of a single-slot PCIe GPU enables new use cases at the edge.
For instance in robotics, autonomous vehicles, satellites, a bit of everywhere. So this is what quantum business is, a company that envisions a future of small compact quantum accelerators deployed everywhere.
Yuval: What is the underlying technology?
Andrea: Yeah, the underlay technology is NV centered [nitrogen-vacancy centers]. Basically our qubits are built out of defects in otherwise perfect carbon structure. The fact that the qubits are inside this carbon structure protects them very much from a lot of noise sources and environmental disturbances. And that’s what really enables NV centers to be used as qubits at room temperature. It allows for long enough coherence time. You don’t need to cool down to cryogenic temperature or anything like that. And if I may say something more about that, NV centers have been around for decades now, have been used in research at universities, academia, they’ve been used in sensors. Really what was the challenging part to make it a quantum computer is deterministic placement of these defects.
Because at the moment, or at least so far, until Quantum Brilliance came out with its inventions, the technology to build NV centers was basically stochastic. So you just like basically stochastically get some NV, some qubits if you want, here and there with spin aligning in a random direction. And you just need to hope that there are two very close to each other and then you have two qubits. But our innovations are really the key for Quantum Brilliance to be able to predict this future of small computers running at room temperatures based on NV centers is the fact that we have IP proprietary innovations in two areas. One is the fabrication at the nanoscale. The qubits need to be really well spaced at a very small and specific distance from each other to enable entanglement but not disturbance as well as scalable nanoelectronics. In these two areas, we have made innovations that are proprietary and that enable us literally to build this type of technology.
Yuval: You mentioned scalable nanoelectronics, and that leads me to my question of how do you control these qubits?
Andrea: So yes, that’s a very good question. It’s like I said, there are two areas of innovation because it seems that if we can solve nanoscale fabrication, which is already a challenging enough problem, then one is done, but one is not done. Obviously. The other area of innovation is in fact scalable nanoelectronics. As of today, for small qubit numbers and for sort of benchtop experiments or academic research, the typical ways to address qubits is by using microwaves and then basically focus microscopes for reading the qubits. This is obviously something that does not scale, it definitely does not scale into a chip. So we had to deliver some innovation there because when you think about placing many qubits next to each other at a very small scale, obviously having to address them individually, as per definition of a quantum computer, it requires something new, innovative that can be based on a chip. And we have done some innovation invention in the field of photoelectric readout.
And that’s what enables us to put these nanoelectronics layers on top of the diamonds and microelectronics on top of the nanoelectronics. And then the photonics layer, the magnetic layers, everything packed into one single chip. I can’t say more about how we do it; hopefully that answers your question.
Yuval: How many qubits do you have today on a chip?
Andrea: Yeah, so today, like I said a minute ago, today we have only a small number of qubits. We only have two qubits, and those are NOCs on this type of chip that I’ve just described. These qubits are on a small diamond the size of 1 millimeter by 1 millimeter by half a millimeter thickness. So it’s really, really tiny. But we are still using confocal microscopes for the readout. This is a benchtop experiment that allows us to study the qubits, qubit features, addressability, the integration, how to control them, what is the noise, what are the models, what are the error corrections that are needed, etc. And this has enabled some of our partners to also explore similar aspects of the quantum computing stack. We’re going to move into chip production soon.
The roadmap hasn’t been released yet, but as part of a big contract we have received in Germany from the German Cyber Security Agency, we are going to deliver a mobile quantum computer prototype in less than 24 months. And there will be milestones between now and there with at least two drops of qubits on chip in many more than two. And those are going to be our first functional qubits on chip with the whole stack of microelectronics and magnetics and everything else on the chip itself. So it’s going to come soon.
Yuval: Help me understand. You mentioned that these two qubits you control with a confocal microscope, but that you’re moving away from that. So if the new chip does not use a confocal microscope, then why is it useful to study the behavior of the existing system?
Andrea: Well, the confocal microscope versus photoelectric readout is just a way to read the qubits. But the qubits are the same. The technology is the same physical entity, and therefore you can study and learn pretty much everything about the qubits with this sort of like more accessible, more benchtop kind of experiment.
Yuval: When you talk about structured defects, which is almost a contradiction in terms. But I understand the need. What is the connectivity? How many qubits can each qubit or will each qubit be able to interact with?
Andrea: Maybe I should start from where we want to get to first in terms of commercially-valuable products. By 2029, we want to release the first compact quantum accelerator for commercial use. And this is also very unique to us because we are not aiming at a million qubits on that chip. We are aiming at tens to 100 qubits. So we predicted with some analysis that between 60 and 100 qubits is what one needs to add some commercial value out of these very small, very cheap, very low power consumption devices. The reason why we believe it’s going to be commercially-valuable is because of what we define as quantum utility.
The first real commercially-valuable product we’re going to release is going to have tens to a hundred qubits. How many exactly? And what type of topology and connectivity is something that we are still investigating. We’ve got a line of efforts, very R&D oriented that is focused on not applications but algorithms specifically and the hardware team working very closely with them. So they are basically developing the two things in parallel. And the algorithm team that is working on the commercially-valuable algorithms that can be run on these more qubits devices is going to inform basically the type of topology, connectivity and qubit number. Because it’s important to say that with these atomic scale fabrication techniques and we have freedom to place qubits really whichever shape we want. So qubits meaning defects and therefore that will enable a large flexibility to accommodate whatever are the needs coming from the algorithm discoveries.
Yuval: You mentioned tens to 100 qubits. Can you give me a sense of what kind of algorithm this is? Is this machine learning, is this prediction, or more generally, is this an algorithm that you could I guess run on other types of quantum computers, except that they’re not as small or power efficient and therefore maybe not as portable on the edge? Is that about right?
Andrea: We’ve got three different targets that we are exploring with the quantum migration team. I can’t really disclose quite yet because we are at a bit of critical stage there, but we are talking about algorithms as well as modalities. So we are investigating a bit of everything. So what will come out from this team may not be gate-based, for instance, or maybe gate-based. We are exploring a bit of everything there and there are these three lines of effort that unfortunately I can’t disclose. But hopefully in six months time or so we’re gonna have something to something to announce or to publicly disclose.
Yuval: Do you feel that you’re going to need error correction for this application or not really?
Andrea: It’s a very good question and actually made me remember what I wanted to say about the previous one you asked. I didn’t answer your question about algorithms that we are developing being useful for other technology as well. Yes, potentially, yes. These are algorithms that obviously can be potentially useful for other technologies too. There are two aspects to consider. One is that the commercial value in this first generation of commercially valuable products will really come from the fact that these computers are very small, very cheap and very low power consumption such that you can deploy 10 or 20 or 30 to solve your problems. Other technologies struggle in selling 20 to 30 computers in a single rack with low power consumption that could be making those algorithms not really commercially available for other technology.
And the other aspect to consider is that because of this very tight development between the algorithm team and the quantum hardware team, it may turn out that the modality and the algorithms specifically will be tailored for this first generation of commercially valuable quantum computer, which could also be a bit of a limiting factor. This is only true for the first generation.
Now going back to your other question, which is obviously very interesting. Everybody asks about fault-tolerant quantum computing. Are we considering that, are we considering error correction? Obviously with very low qubit numbers, we are not aiming at fully error corrected architecture or modalities. The power, the commercial value and the power of these type of small quantum computers will come from the fact that are either going to deploy it in parallel, like in tens or more and leveraging the parallel quantum computing advantage there, or that they can be deployed at the edge for instance in very small facilities or in submarines or things like that. Places where otherwise you can’t even imagine to place a standard quantum computer. However, we are building a roadmap for fault-tolerant quantum computing. It’s really too early to talk about that.
But while in the short-medium term we’re going to have this non-error corrected small-qubit number compact quantum accelerator coming out for commercial use, in the medium to long term we are going to have a version that may have many more qubits and error correction techniques that are available to make these small computers fault tolerant.
Yuval: You mentioned that the computer is the size of a lunchbox, but the core itself is about a millimeter cubed. So what’s taking up the rest of the lunchbox?
Andrea: So when I mentioned the 1 millimeter cube, roughly 1 millimeter cube, that’s the size of the diamond itself that we have today. Once we add the nanoelectronics, microelectronics and magnetic and photonics layer, that could get up to the size of maybe a centimeter or two. Still it’s very small with respect to to a matchbox or standard GPU today. Everything else in there is basically the electronics, controller electronics. When I say that it’s going to be the size of a lunchbox, I mean everything is in there. There’s no need for anything else to run the computer except to load it into a PCIe slot or something similar. And all that is needed to run, read and control the qubits is inside there. So basically just control electronics.
Yuval: One would assume that this could ultimately be smaller. Right. A quantum computer in your pocket.
Andrea: That’s a very, very good vision. It’s certainly something that we keep in mind. That’s probably stage three, maybe. It certainly has the power to scale down this type of technology. Right. Because the chip itself is where the quantumness happens and is well patched there. So yes, I guess that it’s just an engineering problem after that. How small can we make the control electronics and how, yes, how small can we make the whole packet? It could may as well end up in a laptop in the future.
Yuval: As you think about the last 12 months, what have you learned about the quantum computing market or NV centers that you didn’t know a year ago?
Andrea: Yeah, so I have to say that in the last 12 months that there have been quite some movements in the market for quantum computing. Companies that are public, they had their share prices going very much high and very much down and then back high. So I have to say that it’s not just hype. I don’t think it’s just hype. I think that there is something happening and that’s proven by the fact that a lot of private investments are still flowing to companies. For instance, QuEra recently closed a very good round. Congratulations to you, you all. But other quantum computing companies also closed quite big rounds recently. So I want to, I want to, yes, I want to just put it there. That is, I don’t believe it’s just hype. I think that there is something and that is some trust and there is something that is coming out. I also think that a lot of the big discoveries that are going to change the market are still happening even though they are not maybe publicized as much as the Google, Microsoft or Amazon’s news. What else I’ve learned, Yeah, I think these are the biggest big takeaways and we’re not entering into quantum winter as people have speculated a year or two ago. I think that the next couple of years are going to be really, really interesting for our industry.
Yuval: You mentioned some big companies and it seems like in the last couple weeks their CEOs got into the habit of opining on when will quantum computers be useful? Do you want to contribute to that discussion?
Andrea: From our point of view, like I said earlier, I think that we are going to have some useful quantum computer in 2029 when we release our first product. I don’t want to really challenge other companies’ roadmaps, but there are multiple companies that are talking about two, three years time and I don’t feel they are really direct competitors for us because our feature is very unique. And the future I envision is one where big quantum computers with millions or billions qubits, they work in hybrid modes together with GPUs, CPUs and also racks of small quantum computers like ours because they’re any more suitable for some specific task. So yes, I think that I will say in the next five years. However the specification needs to be made here is what does it mean useful. For me, useful is that it saves you 5 cents per operation on a specific very well defined use case only that’s already useful. What people have in mind when they say a useful quantum computer or quantum advantage and what’s not is more something like a general-purpose quantum computer that could have to wait a bit longer.
Yuval: What kind of companies are interested in quantum computers at the edge?
Andrea: Edge quantum computing is something that is very, very early, while for most other cases of quantum computers everybody’s talking about them and there is a common understanding of what those use cases are and what quantum computers can be used for. Edge quantum computing is really just us talking about it and we haven’t made a big effort in terms of marketing so far. We’re going to change that very soon. But without that there isn’t much conversation going on really. It’s just really what our own personal reach is at Quantum Brilliance. The typical use cases are obviously you can think about defense and military applications where you know, you have to elaborate information or images, maybe large images need to do quantum machine learning and things like that at the edge without having the possibility to transmit information to a data center or to larger capabilities for different reasons. Maybe you’re in a submarine or maybe you’re in a war zone where you really can’t communicate.
That’s obviously the most obvious use case. But autonomous driving, maybe not the first generation, but a future generation may require some quantum acceleration next to classical acceleration given by GPUs. Satellites may need the same. Our solution, like I said, is very low power consumption. It can make for a much more sustainable and power-efficient solution than using GPU-only acceleration. I like to think about robotics and I like that in general not just the cyborg or humanoid types of robots, but also robots in manufacturing lines where you’ve got maybe to analyze, for instance, defects on parts and you don’t have bandwidth to send images to a large computing capability for analyzing the images. And these are the type of use cases that are most talked about.
Yuval: And last hypothetical, if you could have dinner with one of the quantum greats, dead or alive, who would that person be?
Andrea: I was obviously expecting this question and I couldn’t get an answer no matter how much I thought about it. The two names I got in mind are Richard Feynman, because I’m very fascinated by that figure. Not just from the physics and scientific contributions that he was a genius and had a big role in quantum computing, obviously, but really I think that if I had to choose one, it would probably be Einstein, simply because in the last years he spent so much time trying to find a different explanation to reality that wouldn’t have to involve this crazy quantum physics theories. Would be good to have him to digest where we got to in terms of scientific discoveries and quantum theory and see what he would envision. That would be my opinion, the most interesting person.
Yuval: Wonderful. Andrea, thank you so much for spending some time with me today.
Andrea: Thank you again for the invite, Yuval. It was really a big pleasure.