Please welcome to the stage, President and CEO, Dr. Alan Baratz.
Good morning. Welcome to Qubits 2026 and welcome to beautiful Boca Raton, Florida. It's a real pleasure for me to be here today speaking with all of you, and I very much appreciate you all taking the time to be here with us today, especially those of you that had to deal with weather and delayed travel.
We have a lot to talk about today. So over the course of roughly the next hour and a half, we're going to cover everything from technology through to business growth. And I think you're going to find it really interesting and really exciting.
So 2025 was the International Year of Quantum, and a lot of progress was made over the course of the year. We saw technology progress with, for example, Google's Willow demonstration — the first time that anybody had actually shown that gate model error correction can work — to increasing qubit fidelities, to new ways of doing error correction like dual rail or QLDPC.
We also saw a lot of business progress. We saw a growth in cloud-based sales and growth in system sales. And of course, for the public quantum companies — the independent public quantum companies — we saw a dramatic increase in valuation, ending the year with a combined $37 billion value across the four public independent quantum computing companies, over a 100% increase.
It was also a very important year for D-Wave. First of all, we launched our Advantage2 quantum computer, arguably the largest and most powerful quantum computer in the world with over 4,500 qubits. We demonstrated for the first time ever quantum supremacy on a useful real-world problem using that quantum computer. We saw multiple customers move applications into production using our systems in support of their daily business operations.
And we saw system sales. We saw the first sale of an Advantage2 quantum computer to the ULIC supercomputing center in Germany. And we saw the purchase of 50% capacity of an Advantage2 quantum computer as part of the Q Alliance in Cineca, Italy. And of course we culminated the year — well, actually it slipped into the first week of this year — by announcing the acquisition of Quantum Circuits, which brings very important revolutionary gate model quantum computing technology to D-Wave.
And as a result, the quantum game just changed. D-Wave is now the world's leading quantum computing company. We were always the world's leading annealing quantum computing company — the only company that has annealing systems that have achieved supremacy and that can support commercial business operations. But now with the acquisition of Quantum Circuits, we have moved D-Wave to a leadership position in gate model quantum computing as well. And you're going to hear quite a bit more about that over the course of the coming hour and a half.
But as a result, we believe that 2026 will be the International Year for D-Wave Quantum. We will continue to make significant progress on our annealing quantum systems toward a 100,000-qubit system. You will see significant progress in the gate model arena. We already have an 8-qubit gate model system operational in New Haven, Connecticut. We'll have a 17-qubit version of that processor available later this year, and both commercial in the marketplace.
You will see progress on large enterprise quantum compute as a service deals. In fact, we just closed one for $10 million — our first large enterprise quantum compute as a service deal. You'll see continued progress in system sales. We just announced that we have sold a system to Florida Atlantic University here in Boca Raton for $20 million, and increasing U.S. government interest in D-Wave and adoption of D-Wave technology, both annealing and gate model.
So D-Wave is now the only quantum computing company in the world that has a dual platform strategy — both annealing and gate. What this means is that we are the only quantum computing company that can address the full market for quantum. In some sense, it also means that overnight we doubled the total addressable market that D-Wave can address, going from primarily annealing to now annealing and gate. It also means that we are now customers' one-stop shop for quantum computing. If you have use cases that require annealing, we've got you covered.
If you have use cases that require gate, we've got you covered there as well. And we're already starting to see some synergies between the two, as some of our annealing customers have expressed an interest in learning more about our new gate model systems because they have use cases that they believe can benefit from that technology as well.
And that means that we now have a very comprehensive product roadmap: annealing, gate, and software. On the annealing front, we've talked about this before. Our Advantage2 system is in the market today. An Advantage2 performance update will be available shortly, providing some really exciting new features like reverse anneal, multi-color annealing, the ability to incorporate some digital controls into the analog fabric, on the way to that 100,000-qubit Advantage3 system.
On the gate model side, I already mentioned we have an 8-qubit system operational today. We will have a 17-qubit system before the end of this year, 49 qubits next year, 181 qubits the following year, on the way to a fully scaled error-corrected system with 100 logical qubits. And from a software perspective, we continue to make great progress with our Leap hybrid solver. We now have the Acumen software platform for supporting the gate model systems. We will be integrating the software environment and the systems into our Leap cloud service, and we'll be working on how to best integrate our quantum systems, both annealing and gate, into high-performance computing environments.
So today, as I mentioned, we are commercial. We are delivering real value, real ROI to customers in helping them to solve important business applications. In some cases reducing time to solve, in some cases improving solutions, in some cases reducing the cost to solve — but in all cases helping to drive better decision making and improved operational excellence. And that is today. Not two years, three years, five years, ten years, but right now, today, that is happening, as evidenced by, as I mentioned previously, a $10 million two-year enterprise quantum compute as a service agreement with a customer to support multiple applications, including moving into production over the next two years.
As we look to the future, there are revolutionary problems that we know are on the horizon that need to be solved, waiting to be solved, and can only be solved by quantum computing. This is where both our annealing and our gate model systems will be able to deliver value, but especially on the gate model side as we look at things like quantum chemistry to be able to develop designer drugs and improve patient outcomes, or new materials development, for example developing everlasting batteries or very lightweight airframes, global weather modeling. These are the revolutionary applications that will be enabled over time.
So let's talk for a minute about the acquisition of Quantum Circuits. This is a perfect marriage. D-Wave is the world's leading annealing quantum computing company — the first to demonstrate quantum supremacy on a useful problem and the first truly commercial quantum computing company, admittedly mostly on the annealing side. Quantum Circuits brings to us three decades — three decades of superconducting gate model technology breakthroughs, primarily done at Yale University and then brought into Quantum Circuits as a spin-out of Yale.
This is a world-leading developer of gate model technology that we believe will catapult D-Wave to the forefront in the gate model arena. And we're going to spend some time now talking about what that acquisition is really all about, why it's so revolutionary, and why it's so transformational.
In just a minute, there are two people that are going to join me on stage: Trevor Lanting, our Chief Development Officer at D-Wave, and Robert Schoelkopf. Rob is the founding director of the Yale Quantum Institute. He's Sterling Professor of Applied Physics at Yale. He's a member of the National Academy of Sciences, and he's now D-Wave Chief Scientist. He's an award-winning expert in the field of superconducting quantum computing with practical error correction. In fact, Rob is responsible for the development of the transmon qubit, which is what pretty much everybody in the superconducting gate model space is using today.
But Rob knew there was a better way, and his work has led to the dual rail qubit, around which he founded Quantum Circuits, which is now a part of D-Wave. So with that, I'd like to ask Rob and Trevor to join me here on stage.
Hi Rob. Trevor. Okay, Rob's going to start by spending a few minutes talking about the dual rail qubit technology and the significance and importance. Rob,
Thanks, Alan. So, at Quantum Circuits, now D-Wave New Haven, we've created an entirely new paradigm for superconducting qubits that we call the dual rail. The dual rail is unique because it's something called an erasure qubit, which means that as a composite object, it can actually detect in the hardware when errors occur. So, let me just sketch out for you how that works.
What we do is we store the quantum information as a single microwave photon that's in one of two superconducting resonators, say left and right, and then you have a zero and you have a one. But the dominant errors are that occasionally the photon is lost, and we're able to detect that and know, sort of individually at the hardware level, when an error occurs in the device.
This gives a sort of dual-use approach for these qubits. First, they function as very high-performance individual physical qubits after you post-select away the dominant errors. The second is this extra information that you gain by knowing when errors occur allows you to use them in error correction codes and gives us a faster and more efficient path to fully fault-tolerant quantum computers. And it's been really exciting. This is a brand new concept, just a couple of years old, but it's made very rapid advances, and we already have our prototype Seeker system with eight dual rails that's functioning in New Haven and is in the hands of our alpha customers.
So let me tell you a little bit more about sort of how to compare this new modality with the other types of quantum systems that are out there. So two of the critical metrics for a gate model system are the execution speed and the performance, the fidelity of the operations. And typically the different types of qubits fall into one of two corners. You have ions or neutral atoms that can have inherently high fidelities, good performance, but they suffer from a rather slow millisecond clock speed.
On the other hand, you have the traditional superconducting approaches that are microsecond clock speeds, much faster, but are typically rather error-prone. And the dual rail, as you see, lies in this sort of most desirable quadrant where we have the fidelity and the performance that you usually associate with the trapped ions, let's say, but with the speed and the scalability of superconducting platforms. So we're really excited about this combination. The dual rail is in a position where it's really time to accelerate our development and begin scaling these systems aggressively. And with this combination with D-Wave and our new family, we're really excited to be able to make rapid progress on that roadmap.
Thanks, Rob. Yeah, but it's not just about error correction. We're talking about needing many, many qubits to be commercially viable. So we have to worry about scaling and other factors as well. And Trevor now is going to spend a few minutes talking about some of the other technologies that we've been working on at D-Wave to bring together with the dual rail technology to really accelerate gate model progress. Trevor,
Thanks, Alan, and thanks, Rob. One of the things that we're incredibly excited about is that D-Wave brings technology and Quantum Circuits brings technology, and there's a real synergy between these technologies that will allow us to be the first to bring to market a scaled, error-corrected gate model quantum computer. Superconducting approaches have an inherent long-term advantage. We can engineer strong interactions between superconducting devices. And as Rob said, this means that we have fast state operations, up to a thousand times faster than some of the other qubit modalities.
At D-Wave, from the beginning in our annealing development effort, we've invested in on-chip cryogenic control, and we're starting to invest in high-performance superconducting interconnects that will interconnect integrated circuits together. Both of these critical technologies are going to unlock large-scale annealing processors, and we're adapting them for the dual rail technology as well.
Rob spoke about the advantages of the dual rail approach. Really what this offers is the ability to detect errors and really drive up your fidelities, as well as being able to encode logical qubits with up to an order of magnitude fewer physical qubits. This is a game-changing technology, and we're incredibly excited to scale it out. And finally, we put an incredible amount of resources into engineering our cryogenic platforms to run for a long time, for years at a time, in customer data centers with high uptime and high availability. All four of these technologies now are part of D-Wave as part of our combination, and these are all critical to build and scale error-corrected gate model systems. We believe D-Wave will deliver this first.
I just want to say a few words about this advantage in error correction and encoding. Dual rail qubits offer a faster path to error correction. What I'm showing in the plot in the middle, along the y-axis, is logical qubit error rate. You want to drive this as close to zero as possible. And on the x-axis is the physical qubits required to build a logical qubit — the number of physical qubits you're using to encode. As you add physical qubits, you actually drive down those error rates, but the goal is you'd want to minimize the number of physical qubits required. Dual rail technology allows us to do this with up to an order of magnitude fewer physical qubits than other approaches.
We're also bringing and adapting our on-chip cryogenic control that has enabled us to scale our annealing architectures. We're adapting this to control the dual rail technology, and this is fundamentally important. As this technology scales, we want to keep the number of control lines required to control the qubits relatively fixed. And our on-chip control for our annealing architectures allows us to reduce the control line counts for our qubit architectures by orders of magnitude. And we're working to adapt this for the dual rail technology.
Alan said a few words about the Acumen software stack. We're actually very excited about the software stack as well. We have a full product suite for operating and developing on dual rail systems. So if you're a developer writing a quantum program and you're used to, for example, programming in Qiskit, we have an API that allows you to continue to develop in Qiskit and run on the dual rail platforms. But in addition, there are APIs that allow users to make unique advantage of the capabilities of dual rail qubits and really the fundamental error gates and the error detection handling. So we have a comprehensive tool set for doing this development.
This technology is, like Rob said, available to alpha users in the cloud. There's cloud orchestration that really offers dual rail quantum computing as a service. In addition, there are some proprietary compilers that really allow you to take those quantum programs, compile them into machine executables or gate executables, and then deploy them to either dual rail hardware or a very high-performance simulator.
As we work to integrate these technologies, as Alan said, we want to make these dual rail solvers and this technology integrated and available in our Leap cloud platform. And we want to make the full tool set, the software development kit for doing the development, available to all of our users in the Ocean software development kit.
Thanks, Trevor. Cheers. And Rob, welcome to D-Wave. Thank you. Exciting.
So I briefly mentioned the gate model roadmap. I just wanted to say a little bit more about it. As I mentioned and as Rob mentioned, there is today an 8-qubit dual rail system operational in New Haven, a complete software development kit, software suite for programming and utilizing that system, including the ability to develop algorithms that leverage the error awareness of the dual rail qubits.
Later this year, we will have a 17-qubit version of that system available with a first demonstration of how error correction could work leveraging the dual rail qubits. We will also have these systems available in the Leap quantum cloud service alongside our annealing systems, and with every new generation of gate model system, it will be an integrated part of the Leap cloud environment. We will also, over the course of this year, bring the Acumen software stack into the Leap cloud platform as well.
In 2027, we will have a 49-qubit version of the dual rail system and the initial build of a 181-qubit version. And then in 2028, we will have the 181-qubit version generally available. This will be a very interesting system in that you could run it either as 181 qubits with error detection for developing new software tools, new algorithms, potentially identifying near-term use cases that could benefit from this technology. I mean, think of this as post-NISQ. This is the first generation of quantum computer that's beyond NISQ — not yet full error correction, but beyond NISQ — or you can run this system configured as four logical qubits.
By 2028, we will also have designed the 1,000-qubit version of this system, which we expect will take a couple of years to build out. And then by then, call it 2030, we'll have designed the 5,000 to 10,000-qubit version with a couple of years to build out. And by the time we get there, we think that we will be converging on 100 logical qubits, error-corrected qubits, which is the bar for commercial gate model quantum computing.
And again, these will be superconducting systems, which means they run at superconducting speeds, a thousand times faster than any of the other modalities. So why would you ever want one of the others? Who wants a slow quantum computer? But they will be fully error corrected and scaled efficiently because of the efficiency in how dual rail does error correction.
So we actually think that despite the hype and the empty promises that you hear, D-Wave has the technology to be the first to market with a scaled, error-corrected gate model quantum computer, and that will be while continuing to serve as the world's leading annealing quantum computing company. So let me spend just a few minutes talking about our annealing systems. As I said, we also have a very strong roadmap for our annealing quantum computers, with the target for Advantage3 being 100,000 qubits.
There are a few things that are critical to achieving that goal. Advantage3 will be our first multi-chip quantum computer. Up until now, we've scaled by putting more qubits on a chip. With Advantage3, we will be interconnecting the processor chips to scale through multiple processor chips, which is why we believe that we can get a 20-fold increase in qubits in one product cycle. Remember, our current Advantage2 processors are 4,500 qubits. So 20 to 25 processors interconnected gets us to 100,000. That's very doable for us.
But we need some technologies to make it happen. We need to be able to interconnect the processor chips and preserve the superconducting and quantum properties between them. And we've been working with JPL, the Jet Propulsion Lab, on the fabrication process to be able to do this bonding. We actually have it operational now. In fact, we've recently used it in a gate model demonstration of bonding a control chip to a qubit chip without loss of fidelity. But we have that process operational now to be used in our annealing systems.
We also need to make sure that with a 20-fold increase in qubits, we don't have a 20-fold increase in control lines. We control 4,500 qubits today with a little over 200 control lines. When we go to 100,000, we can't grow to thousands of control lines. That's a brute force approach. It's not going to fly. Frankly, that's what many of the gate model companies are talking about. It isn't going to work.
What we've done is worked on the architecture for our on-chip cryogenic control to be able to control 100,000 qubits with just 300 I/O lines. This is related to the chart that Trevor showed you a few minutes ago. So building out the critical technologies for the 100,000-qubit annealing system, and we're well down the path on that.
And these annealing systems are being used to support a broad array of commercial applications, but they're also now starting to be used for some very transformational applications. Two that I'll mention, and I've talked about them in the past, are AI and blockchain.
Our annealing quantum computers are the first quantum computers that have been used commercially for large language model training. This was work done by Shinogi, previously the pharmaceutical division of Japan Tobacco. They built a large language model classically trained for generating new molecular structures for human drugs. Then they redid the training leveraging our quantum computer.
The graph that you see in the center is the results from that new model. You can see that on multiple dimensions, the molecular structures generated using the model trained with our quantum computer are better than what was obtained purely classically. Especially the middle graph, the lipophilicity. This is the ability of a compound to dissolve in fats, oils, and lipids. This is key to human drugs that work, and these structures that are being generated are far more well-suited to human drugs.
And then in the blockchain — and by the way, that's just the beginning on AI. I mean, we're doing work in our labs today on how to leverage our quantum systems across a variety of different AI model training architectures, starting to show very promising results. At the end of the day, we think this will deliver better models trained faster with significantly less electricity consumption. So let's stop the craziness about all the nuclear power plants, right? I mean, we think that there's a better way to get there, and that quantum will help us to get there.
Then there's blockchain. I've talked about this in the past as well. All I will say is that we are working with a partner on a quantum-hybrid blockchain that's going into testing this quarter. We'll see how it goes. It'll be a new token, and if the testing goes well, you may at some time during the course of the year see an announcement about a new token launched leveraging D-Wave quantum computers.
And then there's our hybrid solvers. Our hybrid solvers are critical to the commercial application development work that we do with our customers. Our flagship solver is called the Leap Hybrid Solver. We used to call it the nonlinear solver, but we decided we needed a better name. So it's now called the Leap Hybrid Solver. This is a groundbreaking solver in the sense that it brings together multiple different technologies required for solving hard optimization problems. Obviously, we leverage our quantum computers. We leverage mixed integer linear programming, tensor networks, lists, sets, other combinatorial variables.
And the graph on the right is just one example of the kinds of results that we are getting with the Leap solver. This is a satellite placement application. And what you want to do is you want to place the satellites to minimize the gap between the satellites. The gap is on the vertical axis, lower is better. And then across the horizontal axis, number of satellites we're placing. And you can see in blue the Leap solver at different run times: 5 seconds, 30 seconds, 60 seconds. In orange, you see the classical solver that's typically used today for solving these types of problems, run at the longest runtime, 60 seconds. The Leap solver blows it away.
And this is what we'd hope for and what we'd expect. But we've also just announced something I think revolutionary for this hybrid solver. The expressive power of this solver when you program it has grown dramatically since we first launched it, to the point where now you can actually use ML models as a part of the optimization function and the constraints. So, you know, if you don't actually have the data, you can use models that generate it and incorporate that into the functions for the solver, which is quite revolutionary.
Okay, what I'd like to do now is show a quick demo. And so I'd like for Alex Candello to join me on stage. Alex is our Vice President of Algorithms, Performance, and Tools here at D-Wave. Alex,
everyone. For those of you that have been to Qubits previously, you'll know that it's quite common for Alex to join me on stage. Alex is responsible for the team that has developed the Leap solver, also does all our performance benchmarking, develops new algorithms and applications, and Alex is going to walk us through a demo of some work that we did with North Wales Police.
That's right. Thanks, Alan. Hey, everyone. So today I'm going to be showing you a demo of some work that we did as part of a proof of technology with the North Wales Police Department. The North Wales Police Department, as you might imagine, is responsible for policing in the north part of Wales. It's well named.
Specifically, though, as time has gone on, the complexity of the challenges of determining where to deploy their assets and resources to provide geographic coverage while also responding to incidents has gotten to the point that they are considering technologies like quantum computing to accelerate their problem solving. So this is going to be a demo of a project we did with them to experiment with that.
What you see on the map here is one of the regions the North Wales Police are responsible for. They have several other regions in addition, and they've run these sorts of experiments on them, but for the demo today, we're going to be concerned with this one here. This region is split up into 20 different wards that all have incidents reported. They need to be covered. They need to be patrolled.
On the map, you can see in color these little sort of house icons. Each of those house icons corresponds to a station. And each of these stations has a set of assets available to it. So for instance, Station 8 in purple up there in sort of the top right has two day staff, six night staff, and two vehicles available to it. Whereas Station 11 in red actually has no day staff, no night staff, and no vehicles.
So, Alex, I hate to say this, but four stations, you know, four day staff, four night staff — that doesn't sound like a large complicated problem.
Totally. Okay. So, what makes this problem challenging? There's actually three different challenges that I'm going to talk about over the course of this demo. But the first one that I want to address is the size of the solution space that we need to explore with the solver. Each station has a different number of staff, vehicles, day and night. So there's a combinatorial explosion there. Each staff can be assigned to a different number of vehicles for a different length of shift. These vehicles can be placed in many different locations on the map. There's a different set of incidents, which I'll get to in a moment, that they have to respond to.
All of this creates a combinatorial explosion in the solution space, which is exactly the type of problem that our solver excels on — a large, rugged, discrete, combinatorially large solution space, which is why we tried to solve this.
So as I alluded to just a moment ago, beyond just the stations and providing a large degree of geographic coverage, there's also a set of incidents that we need to respond to. So each of these little black markers with the little target on it corresponds to an actual incident that occurred March 5th — I always get the date wrong — in 2015. So we are working with real data here, albeit historical data.
So our challenge is to allocate these assets to provide a high degree of coverage over this while also responding to these incidents in a small amount of time. So I'm actually going to go ahead and kick off a run of the solver. And while that's running, I'm going to tell you about the second major challenge that makes this problem difficult. And that is in the constrained part of it. So the first part was the size of the solution space. The second part is the constraints.
Each of these vehicles — each of these staff rather in a vehicle — can spend a maximum of four hours in the field. Each response, each target needs to be responded to within 20 minutes of that response. There's a total length of shift that is allowed for each of these folks, and all of these constraints together create a very challenging problem for the solver.
So as always, this demo was done live. So while I was talking, we actually ran live on our Leap solver, as Alan alluded to, and here is a schedule that was determined by our solver. So you can see that at midnight on the schedule that we devised, three of the vehicles were home at their stations. That's why they're color-coded and currently sort of faded a little bit. Whereas one of the vehicles was out on patrol.
If we sort of click through the day, and we'll see how good I am at finding specific times. At 10:00 a.m., you can actually see that all four vehicles were out on patrol, and one of the vehicles, this one down here in the bottom right, was responding to an incident.
Further, if we go to — let's see if I can find 2 p.m. because normally that's pretty reliable for having a challenging bit here. At 2 p.m., you actually see an example of one more thing, and this is really the thing that truly makes this problem challenging and truly requires our nonlinear solver. You will notice that one of our cars —
Sorry, our Leap Hybrid Solver, which happens to be a nonlinear solver. Thank you, Alan. You can see that one of our vehicles is responding to two different incidents. Doesn't seem like such a big deal, right? Well, actually, if you try to model this problem, you're going to run into a challenge, which is that, remember, we're trying to minimize our incident response time.
So in the best case scenario, this top line, you have a car, maybe it's left the station or it's finished its last incident response. It's sitting idle. A call comes in to respond to an incident. It immediately drives, arrives at the incident, is able to respond. This response time is just the drive time in that case. Easy peasy, no problem.
But there is another case, and it's more challenging, which is that you are not currently available to respond. You respond, you're currently working on another incident, but the clock doesn't stop just waiting for you. The clock has to start when the call came in. So the total time of response is the time till completion plus the drive time.
So this doesn't seem so complicated, but in order to model this, you need a max function. It's just the max of these two times. No problem. Except that I need to tell you that all of our classical competitors don't encode a max function. This is a nonlinear function, which is a capability that our solver can do, which is why we're able to solve this problem.
So finally, I want to leave you with the overall results as reported by North Wales Police. So for the schedules that we were generating for them, we were able to generate them faster. We were able to slightly improve the incident meeting goal, which is great. But crucially, we were able to reduce the response time by almost 50%. Six minutes might not seem like a lot, but in the context of a police response, say that there's a domestic violent incident or something like that, six minutes is an absolute eternity. And so driving this number down was absolutely crucial for them.
So with that, I'm going to turn it back to Alan. Thanks, everyone.
And of course, saving lives is what it's all about. And we're really proud to have been a part of this effort.
Okay. So a recent study, 2025, by Wakefield Research indicated that 81% of executives feel like they've basically hit the limit with respect to what classical computing can do to solve their hard optimization problems. And by the way, business optimization problems represent most of the important problems that businesses need to solve.
But with D-Wave's annealing technology today, gate model in the future, and with our Leap solver and our amazing services team that helps our customers to build and deploy applications, we're making enormous progress across the board in helping businesses leverage this technology to benefit their operations.
We're now working with one of the world's largest U.S. international airline carriers on problems that you might imagine, things like crew scheduling or plane routing. We're working with one of the world's largest chemical companies, BASF, on optimizing how they operate on their plant floor to fulfill orders, reducing the time to optimize the scheduling from 10 hours down to just seconds.
We're working with one of the world's leading mobile carriers, NTT Docomo. We've talked about this in the past, to basically optimize cell tower resources and increase the number of phones that can be supported per tower. And we're working with one of the world's largest payment companies on a variety of applications, including customer loyalty reward program optimization.
So, what I'd like to do now is spend a little time talking to some of our customers and hearing what they have to say about D-Wave, our products, and our technologies. What I'd like to do is start with Troy Craig, who's the VP of Software Engineering in the Optum Growth Office. Troy, if you could join me,
welcome to Qubits.
Thank you. Excited to be here.
So, I know it's hard to believe, but some people might not know who Optum is or, you know, how it relates to UnitedHealth Group. So maybe you could just start there.
Sure. Optum is a healthcare services and technology organization that sits inside of our parent company, UnitedHealth Group, with a focus on providing healthcare services and technology to improve the overall experience.
And obviously healthcare deals with large, complex problems, and you know, I think that you believe that classical is starting to struggle to keep up. So maybe you could talk about, you know, why quantum.
Yeah, healthcare is full of a lot of large, time-based and data-heavy problems where we're hitting current limitations based on the traditional models that are available today. We believe quantum could be an unlock to attack these problems differently and see some advancements across the overall healthcare system.
So, you know, we spent some time working with your team. How did it go?
Yeah, Optum is constantly evaluating emerging technologies and partners, and in that we see D-Wave as a strong partner in the quantum space, and it's something we're really excited about.
And where do we go from here?
Yeah, continuing to identify the right problems to attack with quantum is where I see our teams coming together and really focusing our time and energy on those big ones where quantum is the right fit.
And you think we'll get to production deployment?
Very, very excited and optimistic.
We've had the opportunity to speak with Dale Moore from Davidson Technologies in the past. I'm going to ask him to join me on stage again in just a minute. But Dale Moore is the President and CEO of Davidson Technologies. And we also have here, actually through Zoom, Matthew Steeman, who's President and Chief Business Officer at Anduril Industries. And so let me ask Dale to join me on stage, and then we'll see if we can get Matthew up on the screen.
And there he is.
Good to see you.
So, first of all, let me say that Davidson is celebrating their 30th anniversary, Dale. That's an amazing achievement, and I just wanted to congratulate you on that.
Thank you. We're excited. It's a big year for us.
And we're looking forward to helping you make it even better years going forward. So, Dale, you know, there's been a collaboration between Davidson, Anduril, and D-Wave. Maybe you can start by talking a little bit about that and what makes it so unique.
Yeah. So I think, you know, this is my fourth Qubits, Alan, and you know, we've been up here before talking about different aspects of how we want to apply quantum technology to the use cases that our customers care about. Our mission is very simple: innovate with purpose, deliver with speed, and empower the warfighter.
When you take that vision and that mission and combine it with the operational excellence of what Anduril is providing to their customers today, it really brings a different level to the applications that we're trying to develop. And so this collaboration, from my perspective, is really, really important and unique to the national security space.
And again, in the world that we live in, the problem sets are only getting more complex. And when you underpin all of the different solutions that are already out there for doing different things in our space with the ability and the capability of a quantum-based approach, particularly in the optimization of decision support mechanisms, it really drives what we believe is going to be a foundational technology for the future of the national security environment.
And I couldn't ask for a better partner than Anduril and D-Wave for that matter. And bringing the best of these three companies together and what we do well, I think is going to prove out to be a game-changing event.
Yeah, very exciting. Thanks, Dale. And Matt, you know, we've had the chance to hear from Dale in the past, so I think most of the people here know a bit about Davidson. Maybe you could just spend a minute talking about Anduril, but then, you know, maybe tell us what's the most surprising thing you've learned from the initial collaboration.
Sure. Well, first, apologies for not being able to make it there. I'm hoping that one day quantum can solve the intractable D.C. snowplow optimization problem. We're a bit iced over here, but thank you for having me.
Yeah, first, Anduril, we're about eight years old, 7,000 people. We build mainly advanced robotics and the software systems that power those robotics for the national security community. You know, I think when we started the company, I wouldn't have said that quantum would have been on our bingo card. That was eight years ago. You know, five years ago, probably not. But about two years ago, I think the technology matured to the point where we started to believe there was a national security application today.
And so for us, we're not an S&T company, we're an integrator, and so we generally focus on higher maturity technologies. So in our space, we call that technology readiness level. So think TRL like 5, 6. How do we get that to a nine into full fielding. You know, maybe two years ago, we kicked off a campaign to really start to understand quantum optimization, its impact on what we do.
I have been shocked at how fast and mature the technology has been to deliver actual useful results to the problem sets that we're working on. I'm not going to spoil what those are. One of my colleagues will speak later today in depth about some of the problems. The topic area is broadly missile defense and sort of the optimization in terms of sensing and affecting within that domain.
You know, but for me, I'm not a quantum expert, a computer scientist by background, engineer by background. My biggest shock has been this stuff is ready. It's ready to use today, and we're going to continue to use it with our partners and with the national security community to its greatest effect possible.
And Matt, what has been the response to quantum from the defense industry?
I would say it's probably similar to our own, where it's sort of moved, I think again over the last 24 months or so, from this like kind of realm of 'I don't believe it, science fiction' to 'okay, it's here, it's now.' You know, many in the audience probably know the government has mandated a shift to post-quantum crypto by 2030. So the government clearly believes that we're moving from S&T into R&D into full fielding and up the value chain in the government's terms in four years.
And so I think broadly within the community that I work in, we all now have to be prepared to integrate these types of technologies into everything.
That we do. Yeah. So Matt and Department of War, welcome to D-Wave. Dale, why should the US government prioritize quantum computing investment?
Well, Alan, I think it's clear, and I mentioned this earlier, you know, the threats that we deal with on a daily basis and the scenarios by which these use cases and problem sets that are national security problems are only getting more and more complex. And so this technology, to Matthew's point, is here today. It is operationally viable. We are at the forefront of applying the technology to problem sets that those customers care about. And so it's about real mission impact, and that's what we're focused on. And I think from the US government's perspective, they're going to have to mature quantum technology and its application in multi-domain space in order to achieve the results that they're looking for and fundamentally stay ahead of some of the near-peer adversaries in the world today. And the geopolitical environment is only getting more complex. Obviously, you know, the proliferation of ballistic missile technology and missile technology as a whole around the world is a critical security risk for the US government. And so our focus, again, of staying ahead of the mission and really delivering value to those customer problems is our focus. And I think quantum is going to be a part of it, and we're excited to leverage our collaborative partnership and fundamentally the platform that's hosted in our facility to help support.
And Matt, just to finish up, where do you see the collaboration going from here in terms of use cases to explore?
Sure. Well, first let me say that none of this works unless all three of our companies bring to bear the right types of subject matter expertise in hardware, in software, algorithm development, domain expertise, the integration of those solutions within the broader national security apparatus. All of this is really complicated. We shouldn't make light of the subject matter either. This is, in most cases, life and death. This sort of changes the balance of US and Western deterrence. Stuff that matters. Maybe people don't — folks that don't work in the national security community, they don't think about it every day. Those that do, this is our lives. This is what we do. The partnership is just going to grow from here. There are an infinite number of optimization problems within the national security community. Missile defense is where we started because we knew that we had a customer that was keen to understand quantum's ability to help in that domain. What's next? Network optimization, other types of pairing problems, other types of logistics challenges and contested logistics within broad areas of operation. We couldn't be more excited about where we are. The fact that we're first past the post on a lot of this stuff with our customers is exciting. It's new, and we're ready to get after it.
Great, Matt. Thanks. Dale, thank you.
Thank you, Alan. And by the way, Dale, it's great that we have the Advantage 2 system now operational at your headquarters in Huntsville and, you know, starting to work on how we secure that thing to be able to run classified applications.
Excited about the future, Alan. Thank you.
Thank you. Thanks, Matt.
Okay, so that was a little bit on applications and use cases leveraging our quantum systems. That work generally goes on through our Leap quantum cloud service where our customers access the systems on an as-needed basis to run their applications. But we're also seeing increasing interest in having on-premises D-Wave systems. The first system that we sold for on-premise installation was sold to the ULIC supercomputing center in Germany. And we've announced another recently, which we'll talk about in a minute, and a third just this morning, which we'll talk about in a minute. So, what I'd like to do right now is I want to welcome a very special guest on stage. In October this past year, 2025, I had the opportunity to participate in Italy's Digital Innovation Forum in Como, Lombardy. That's actually the hometown of our next guest. And at the Digital Innovation Forum, the Q Alliance was born. This is an alliance to bring quantum computing to Italy in support of its digital transformation initiative, workforce development, application development, you know, leveraging quantum systems. So, I'd like you to join me in welcoming from the government of the Italian Republic, Senator Alessio Butti, Under Secretary of State to the Presidency of the Council of Ministers with responsibility for innovation and digital transformation. Senator Butti, welcome.
Thank you. It's a great pleasure to have you here with us. I'm honored to be here with you and your friends.
Thank you. So, I have a few questions that I'd like to ask you, and I'm going to go ahead and ask all the questions and then give you an opportunity to respond.
Yeah. If you want to ask me something, we can start.
Oh, I want to ask you a lot.
I heard before. So, okay.
Well, why don't we go ahead and get started? Okay. So, the questions are: first, why do you see quantum computing as strategic for the Republic of Italy? Second, how does the Q Alliance initiative fit within Italy's national quantum strategy and what role do you see for open public-private collaboration? How will this vision translate into concrete actions? And what are the next steps you foresee, particularly in terms of research centers and national infrastructure? And then you mentioned economic impact. How do you see quantum already delivering value to industry and public administration today? And then finally, what's the importance of international collaboration in quantum computing, especially in the global ecosystem such as the one represented here at Qubits? We have two days to answer all these questions.
No. Five minutes, 10 minutes.
You can take as much time as you want so long as it kind of fits within a reasonable time frame.
I am prepared enough and I thank you. Thank you. Can I use —
Yeah, sure. In fact, would you like me to close this?
Okay. It's better. I thought we had a good relationship.
Thank you, Alan. Thank you for your introduction and questions, but to define our moment, I'm honored to be here with you. I speak on behalf of my government, as you know, and I took some notes and I have prepared some answers. We have a little time for your challenging questions, but I will do my best even with my jet lag. So please bear with me because I come from Rome. First of all, quantum technology represents a structural shift, not a gradual evolution, in how we compute, secure information, and make decisions in critical domains. For Italy, with its strong scientific base and diversified industry, quantum is not optional. It is strategic. This is why we have created a national quantum strategy, as you know. But strategy alone is not enough. What matters most is coordination. Coordination between research, industry, public administration, and international partners so that scientific excellence translates into real-world application, economic impact, and lasting competitiveness. This leads me naturally to Q Alliance, and we strongly support the Q Alliance because we believe in open, transparent, and collaborative models. It is not a closed club nor a top-down structure. Access to real quantum systems, such as those from D-Wave, is essential. Q Alliance already connects major academic institutions from Italy, from Calabria in Cosenza to Federico II University in Naples and Insubria University. This network approach is essential, as no single actor can drive this transformation alone. I'm pleased to see D-Wave among the founders, as real quantum systems are crucial. Quantum must be used, not just studied. Our goal is to move from small, fragmented efforts to real scale. Projects like the VA National Research Center and collaboration with the universities are steps in that direction. I want to clarify: building a center in the Como area is not just for the local region. It will be a national resource, open to everyone and connected internationally. This center will provide access to quantum systems, support algorithm development, train the workforce, and accelerate industrial applications. The key ideas are openness, shared infrastructure, and economic impact. Quantum is often seen as a future promise, but it already has value today, especially in hybrid approaches when combined with classical computing. Italian industry and public institutions can benefit in finance, logistics, energy, healthcare, manufacturing. At the same time, we must train people to use quantum technology effectively. This is fundamental. Building a strong ecosystem means developing technology, skills, applications, and governance together. Finally, quantum by nature is global. International collaboration is essential, especially in our current complicated geopolitical situation. No country can build a full ecosystem alone. Italy wants an open and transparent ecosystem, strong in Europe and open to international partners. I believe in this project, and I'm here also for this. Security and responsible use require working together across borders. We aim to be a reliable partner, and we will do our part. We want to share knowledge, host infrastructure, and enable experiments. And we want to collaborate with allies who share our vision of innovation, responsibility, and long-term values. Q Alliance and events like Qubits 26 show that this approach works. By the way, I look forward to welcoming you in Cerano, Como, for the fourth edition of the Digital Innovation Forum Como Lake 2026, which will take place in October. On that occasion, we will be able to present the work we have accomplished together through our Q Alliance partnership. Are we up to the challenge? I think so. Quantum is more than a technology. It is a political and strategic journey, and Italy is fully committed to this journey. I hope to have answered all your questions. I would like to add that Italy is one of the first European countries to approve a national quantum strategy. I will be talking more about that in my official speech later today, and as you know, my staff, who I would like to thank, is working closely with D-Wave on our alliance. Thank you so much.
