Filed by D-Wave Quantum Inc.

Pursuant to Rule 425 under the Securities Act of 1933

and deemed filed pursuant to Rule 14a-12

under the Securities Exchange Act of 1934

Form S-4 File No. 333-263573

Subject Company: DPCM Capital, Inc.

(Commission File No. 001-39638)

17th Annual Needham Technology & Media Conference Transcript – May 18, 2022

Alan Baratz CEO and John Markovich CFO, D-Wave Systems Inc.

Alan Baratz

That’s why we’re at 5,000 qubits a day when everybody else in the industry basically has selected gate model. And they’re at only about 50 qubits. Annealing is also less sensitive to errors. We’re able to deliver good solutions to hard problems today without the need for error correction. And finally, annealing is very good at solving optimization problems. The kinds of problems I mentioned before, employee scheduling fraud detection, even optimizing cloud deployment through Kubernetes, frankly, most of the important hard problems that businesses are solving today are those optimization problems. And annealing is very good at that. And those are the three reasons why we decided to start with annealing. So what is an annealing quantum computer? An annealing quantum computer basically does only one thing. It finds the lowest point in a multidimensional landscape, but it does it really well. The other thing that’s important about that problem is that any optimization problem can be easily and efficiently mapped into that problem.

Alan Baratz

That’s why annealing quantum computers are so good at solving optimization problems. And that also makes annealing quantum computers easy to program because you don’t have to understand quantum physics. You don’t have to understand linear algebra. It’s just about mapping your problem into the problem that the annealing quantum computer solves and that’s allowed us to become commercial today. Gate model on the other hand is programmed by actually specifying the sequence of instructions needed to solve the problem. But these instructions are very complicated and that’s why there’s a very steep learning curve to programming a gate model. Quantum computers that run gate model systems are very sensitive to errors. They are really going to require error correction in order to be able to solve real business problems at commercial scale. And we believe it’s going to be seven or more years before we get to a point where a gate model system is actually able to solve business problems at commercial scale, however, gate model systems are very important because they can solve differential equations problems.

Alan Baratz

And differential equations are required for things like quantum chemistry or computational fluid dynamics, very important application areas. Now we learned something very interesting, unexpected, and important about eight months ago. At that point in time, it was proven theoretically and demonstrated experimentally that while gate model systems are very good at solving differential equations problems, they cannot deliver a speed up and likely never will deliver a speed up on optimization problems. And while annealing quantum computers are very good at solving optimization problems, they cannot solve differential equations problems, which means we now understand that there’s a bifurcation in the application market. There are problems that require annealing, and there are problems that require gate model. D-Wave is the only company in the world that delivers annealing

 

-1-


quantum computers. And as a result, the only company in the world that can address those optimization problems.

Alan Baratz

Moreover, we announced about six months ago that D-Wave is now also building a gate model system because there are many things we learned from our annealing systems that we think are going to allow us to move fairly quickly in the gate model space. And as a result, D-Wave will also be the only company in the world, delivering both annealing and gate model systems. Now there are also problems that can be solved equally well on annealing or gate systems. These include things like linear algebra for machine learning or factorization for crypto, but that’s how to think about the quantum computing landscape and why, D-Wave is so different from everybody else in the industry. We’re the only ones doing annealing. Everybody else has done gate model. And while annealing systems are easier to build, it’s still taken us over 10 years to get to the point where we have a commercial quantum computer.

Alan Baratz

It wasn’t until we delivered our 5,000 qubit Advantage system about a year ago that we could solve real business problems at commercial scale. So it’s taken us 10 years to get to this point. Gate model is still in its infancy. We’re seeing only very small, very noisy systems. Really all you can do with them is research experimentation. And it’s going to be many years to get to the point where they can solve commercial problems, where at noisy intermediate scale, we need to start seeing error correction, probably initially partial error correction, partial scaling, and full error correction, full scaling. It’s going to take many years to get there, but at D-Wave we basically have a first mover advantage in the market because we’re out there today, commercial with our annealing quantum computers, building customers and customer loyalty with applications for customers on the path to more powerful annealing systems, as well as gate model systems.

Alan Baratz

On the differentiators for D-Wave: I’ve already talked about the fact that we’re annealing and now the only company that will be doing both annealing and gate. I’ve also mentioned that we are a full stack provider, everything from the computers to the cloud service, to the software development tools, to professional services. Our quantum cloud service leap is very important to us. It was designed not just to support research experimentation, but also business applications in production, building in the availability, security and privacy required to support those applications. We’ve got a proven track record of on-time product delivery, both hardware and software. Our 5,000 qubit Advantage system is our fifth-generation processor. And we’ve demonstrated significant speed up on important real-world problems. I’m not talking about synthetic benchmark problems, which are the domain of gate model systems right now, but real world problems. In fact, the problem reference here, the 3 million times speed up is a magnetic materials phase transition computation.

Alan Baratz

It’s known as the Kosterlitz Thouless phase transition. The theory behind it won the Nobel prize in 2016, and we can perform that computation 3 million times faster on our quantum computer, then it can be performed using Monte Carlo and classical systems, which is the approach of choice for this type of problem. And as I’ve already said, we’ve got a very significant first mover advantage with respect to being commercial. The total addressable market for quantum is large and growing rapidly. These are Boston consulting group numbers. I don’t want to spend a lot of time on it other than to say, BCG puts

 

-2-


the TAM at $2 to $5 billion in near term growing to $450 to $850 billion in roughly the 20 year timeframe. And they do divide that TAM into combinatorial optimization, linear algebra and factorization, and differential equations. The categories I talked about a minute ago, roughly estimate that about 25% of the TAM falls into each of these categories.

Alan Baratz

What that means is the 25% that’s optimization requires annealing and is available to only D-Wave. That portion of the TAM is ours exclusively in the industry because we are the only ones that do annealing. So what has it taken to become commercial? It’s taken commercial products, real applications, a market and adoption. I’ve already talked about the fact that our approach to quantum has allowed us to get to commercial quantum computers. That’s allowing us to build out, as we speak, commercial applications for our customers. And in fact, in, 2021 last year, over two thirds of our quantum compute as a service revenue came from commercial customers. And as I’ve already said, we have more than two dozen global 2000 customers. And over 55 commercial customers in total. We’re focused currently on three industry areas, manufacturing and logistics is the first, pharma is the second.

Alan Baratz

And finance is the third. We’re focused on these three areas because those are the areas that have the important, hard optimization problems. So they’re the low hanging fruit for us and everything you see on this chart is an actual application that we’ve worked on developing for a customer. I talked about packing containers onto rail or ships, or, employee scheduling last mile routing for eCommerce grocery delivery. We’ve done protein folding with GlaxoSmithKline and clinical trials portfolio optimization, fraud detection with PayPal. And so on. I already said that we do have a complete stack that includes our quantum computers. Our current generation quantum computer is our 5,000 qubit Advantage system. That was the first system that allowed us to become commercial. Our quantum cloud service called Leap, which has had over 99% uptime since we launched it back in 2018. And a complete suite of software development tools called Ocean.

Alan Baratz

These tools are available both inside of Leap, no download necessary. You can go to the quantum cloud service and you can develop your applications right there inside of Leap, but the tools are also open source. You can download them, configure your local system, do the programming locally, and then submit the applications up to Leap once they’ve been developed. And finally, our professional services capabilities through what we call our Launch program. This is a four-phase model that we use to work with our customers. The first phase is an application evaluation where we help our customers understand which of their applications can most or best benefit from our quantum systems. We then move on to a proof-of-concept phase, where we build a proof of concept for one of those applications, then a small scale pilot deployment in their environment and finally, full scale production deployment. The first three phases, evaluation through to pilot deployment are professional services oriented, the last phase is full scale production deployment.

Alan Baratz

That is the recurring quantum compute as a service revenue model. I’ve talked about our Leap cloud service a couple of times, and I really want to reinforce the importance of having our own cloud service. Pretty much everybody else in the quantum industry relies on third parties for cloud access. They rely on AWS Braket or Azure Quantum, or Google to provide the cloud based access to their quantum

 

-3-


computers. You can access our quantum computer through AWS Braket, but you cannot access all of the D-Wave functionality through Braket. And we do have our own cloud service through which you can access all of our functionality. The reason for that is if you seed the cloud service to a partner, you are basically losing control of your customer, you have no or limited access to their identity.

Alan Baratz

You have no or limited ability to influence their journey to ensure they have a good experience with your products. And you don’t get to learn from their use of your of your products to be able to improve on an ongoing basis. And then of course, there’s the shared revenue. So the economic model isn’t quite as good by having our own cloud service. We have complete control over our customer, our customer’s journey and the ability to learn from their use of our systems. As I mentioned, our current commercial system is our advantage quantum computer. The big circle on the right is what it looks like. The small circles are basically what’s inside that big box. The bottom small circle gives you a picture of the IO through the refrigerator that allows us to run at superconducting temperatures. The circle above that is the super conducting circuit card. We design and manufacture those ourselves and the chip above that is the quantum processor, the superconducting quantum processor. As you can see, this is all commercial grade technology.

Alan Baratz

This is not, a kind of a mass of unsightly wiring running around inside that box. This is all commercial grade technology. And then finally with respect to our gate model quantum computer, we’re not interested in small toy systems: we’re all about commercial. And so we do not deliver a noisy intermediate scale system. We are going to go straight to a scaled error- corrected gate model system. We have a multi-phase approach to that, and it will take a number of years to get there. But in our first phase, it’s all about fabricating the qubits with high coherence times. We have our first qubits back and cold today, and we are testing coherence times. Then it’s putting control on the same chip as the qubits and being able to maintain the same long coherence times we’ve done with our annealing quantum computers.

Alan Baratz

We’re the only company in the world that has control on the same chip as the qubits. And now we’re moving that to gate model. Then we’ll build a small partially error corrected system, and finally, the fully scaled, fully error-corrected system. We have a complete management team, not just R & D, but Go-to -Market, R & D as well as the GNA functions with really strong experienced people leading each of these areas. Okay, I’m now going to turn it over to John to spend a few minutes on the financials, and then we can open it for Q and A. John.

John Markovich

Thank you, Alan. In preparation for this transaction, we developed a very comprehensive bottoms up five-year financial plan and are projecting a revenue CAGR of a little over 160% over the next five years, coming off a base of $11 million in targeted revenue for 2022. This $11 million represents about a 75% increase over our last year revenue, and entering the year we had approximately 40% of the $11 million. It was supported by firm backlog and contracts that were entered into in prior periods that come up for renewal throughout the year. Internally, we have a number of initiatives to drive this revenue. First is the broadening of our customer base through the expansion of our direct sales organization and our

 

-4-


network of channel partners. And we are planning on directing approximately 25% of the use of proceeds from this transaction to our various Go-to-Market initiatives.

John Markovich

In addition, we will continue to introduce new applications and we are expecting that our customers will expand beyond their initial application. And we’re already starting to see very strong evidence of that. So this is an upsell component of our business model. And, lastly, we are also anticipating that the average transaction size will increase over time as the nature of the problems that we are addressing become increasingly complex. And as our computational power increases with future generations of the annealing system going forward and underpinning these revenue projections is the overall growth in the annealing portion of the TAM. This revenue is just the optimization portion of the TAM that Alan highlighted earlier, it does not include the linear algebra or factorization portions of the TAM, which annealing technology can also address. And it also does not include any contribution from our gate model program.

John Markovich

The growth in the gross margins is driven principally by the gradual shift in the mix of our revenue from what is today, approximately 50% professional services and 50% of recurring quantum computing as a service such that in the fifth year in excess of 90% of our total revenue is anticipated to be the cloud based recurring quantum computing as a service. The direction and magnitude of our EBITDA margins closely correlates with the gross margins due to the high degree of operating leverage. That’s inherent in our business model. And we are anticipating that we’ll turn the corner on sustained positive EBITDA in the second quarter of 2025.

John Markovich

From a cash perspective, the proceeds from this transaction provide us with a fully funded business plan. And over the next couple of years, we will continue to invest very heavily in a variety of different R & D initiatives. Approximately 30% of the use of proceeds will be targeted towards our internal software development. And about 40% of the use of proceeds will be applied towards our systems development with roughly half of that amount being investments in technologies that will support both the gate model and the annealing systems initiatives and about 25% of that will be for the gate model program on a unique basis and in the annealing program on a unique basis. And this is in addition to the 25% of use of proceeds that we will be targeting towards our Go-to-Market initiatives. We are anticipating that we’ll turn the corner on sustained positive free cash flow in the first quarter of 2025.

John Markovich

And we have a very capital efficient business model. It costs less than $2 million to build and fully calibrate one of our annealing systems. And each of those systems will support between 25 and 30 million of revenue on an annual basis. Today, we have three production systems in place. One located at the Burnaby headquarters location in Canada, one in Germany, and very recently we introduced a system in the United States. So we don’t need to build capacity anytime in the near term, although we’re likely to add additional systems before we need them for capacity, for sovereign reasons or for market access.

 

-5-


John Markovich

This is a summary of a bonus structure that we announced when we announced the business combination in early February. The intent of this structure is to incentivize investors to not redeem and it provides a pool of 5 million shares that gets allocated to the non-redeeming shareholders on a pro rata basis. So if you focus on the first column here, you’ll see under a zero redemption scenario that the effective cost basis for the public SPAC shareholders is $8.57. And if we go over four columns to the column, that’s labeled 30%, you’ll see that under a 30% redemption scenario that cost basis lowers to a little over $8, or $8.08 and so on and so forth. In addition to this 5 million share bonus program for the SPAC public shareholders, we also have a separate bonus pool that we will use to adjust the cost basis for our pipe shareholders, such that the pipe shareholders and the public SPAC shareholders enjoy the same cost basis on a per share basis.

Alan Baratz

Thanks, okay. Thanks, John. And, just to wrap it up. So, you know, as I said, D-Wave really is the only commercial quantum computing today. We got there by starting with annealing which is a very important component of the quantum landscape. We actually think that it’s going to be many years before gate model systems will be able to be commercial, which is pretty much what everybody else is pursuing. But for D-Wave, we’re building our business today on annealing and then we’ll slide in the gate model as it becomes available. And it’s just an upsell for us to our current customers to new application use cases. Currently we’re focused more on those evolutionary applications that businesses are solving today, but so hard that they can’t solve them optimally, where we can help them solve them better to deliver significant business benefits on our way to the revolutionary applications.

Alan Baratz

And with that, I will turn it back over to Quinn for Q and A.

Moderator

Great thank you, Alan. Thank you, John. I guess I wanted to start on, on some of the use cases and, and you look at your, your four-phase model. I think it culminates in, in, you know, the quantum computes as a service offering where I believe you’ve said in the past, you can generate, you know, $500,000 to $1 million per application. And so I guess my first question is, as you engage with some of these larger Fortune 500 type customers, how many applications could they ultimately run in, in a given year? I mean, are you engaged on multiple applications? Is it sort of a land and expand strategy where you engage in one? And then they realize, Hey, we’ve got three or four other scheduling or optimization, tasks, and, and it sort of becomes a nice expansion strategy.

Alan Baratz

Yeah. So it it’s very much a land and expand strategy, although it differs a little bit by customer. So let me give you some examples. You know, we engaged with a Canadian grocery chain initially on employee scheduling. Once we had that problem solved, they wanted to work on a last mile routing e-commerce grocery delivery application. And so that’s in process now. GlaxoSmith clients started with codon mapping and then began working on RNA folding. PayPal started with fraud detection and has come back to us with six other applications that they’re interested in working on with us. So, you know, that’s kind of the land and expand model. Now, you know, we’ve got a very large company in Turkey that started and said, we want you to come in and engage with all of our business units and broadly explore the applications that quantum might be able to benefit.

 

-6-


Alan Baratz

So that’s more, all at once. Let’s get, you know, many things going, but that’s not the most common model. The most common model is land and expand.

Moderator

Great. The next question I have is, some of your gate model competitors will claim that they too can run optimization problems and, and so that they can, they can address some of those challenges in, in the future. Why do you think they’re disadvantaged relative to the quantum annealing systems? What problems do they run into solving optimization?

Alan Baratz

Yeah, absolutely. So, you know, first of all, they may claim it only because they know that optimization represents the important problems that quantum can address today. And so they want to be there, but, you know, it has actually been mathematically proven and demonstrated experimentally that gate cannot deliver speed up on optimization problem.

Alan Baratz

This is work that was done by a variety of different researchers, uh, including in the U.S. and in Germany. Researchers, for example, at Google. Basically what was shown was that in order for a gate model system to solve an optimization problem, you need to wrap it with classical compute overhead because gate model systems are not native optimization engines. And what was proven was that the classical overhead required to get the gate model system to solve the optimization problem far outweighs any of the benefit that the gate model system can provide on the optimization problem. In fact, it’s a significant slowdown rather than a speed up. And just to kind of put a finer point on this, the mechanism that has been tried to get gate model systems to solve optimization problem is called QAOA, quantum approximate optimization. Okay. But what we now know is that if you want to solve an exponentially hard problem, a hard optimization problem of size, you need to solve problems just as hard on a classical computer.

Alan Baratz

So in other words, to solve one hard optimization problem on a gate model system, you need to first solve many hard optimization problems on a classical computer, and that drives a significant slow-down and there’s similar, different, but similar results for when you get to error corrected gate model systems. So, they may be saying it, but it’s just been proven that, that it’s not actually fact great.

Moderator

The next question I had you’ve described a quantum annealing system is, is a system that is very efficient at finding the lowest energy state in, in a multidimensional landscape. How does that apply to some of the machine learning or linear algebra and factorization, you know, challenges that quantum computing is, you know, looks like it will be good at solving.

 

-7-


Alan Baratz

Yeah. So first of all, that particular problem that you just described, the low energy state and a multidimensional landscape, uh, it has a classical mathematical formulation it’s called the binary quadratic optimization problem.

Alan Baratz

It is an exponentially hard problem is what’s known as an NP hard problem, which is the hardest of the optimization problems. And it also means that any optimization problem can be reformulated as that problem. And that’s why any optimization problem can essentially be mapped onto the annealing quantum computer. Now, there are problems that you might not think are optimization problems, but they actually are. For example, protein folding actually ends up being an optimization problem, feature selection for machine learning ends up being an optimization problem. Now that particular problem of finding a low energy point in a multidimensional landscape, it can also be reformulated as what’s called a satisfiability problem. Okay. Now I don’t want to get into the details of what a satisfiability problem is, but that’s how you factor large numbers on the D-Wave system. So, essentially the way you factor a large semi prime product of two large primes on a gate model system is by running an algorithm called Shor’s algorithm, which is a fairly complex algorithm. You know, in the best case, it’s estimated that it requires 20 million qubits to be able to run Shor’s algorithm on a 2000 bit semi prime, which is state of the art for the RSA public key crypto system, 20 million qubits. You factor on an annealing system differently.

Alan Baratz

You factor on an annealing system by turning the factoring problem into a satisfiability problem and then mapping that into the problem that the annealing quantum computer can solve. And the annealing computer’s pretty good at that. In fact, the largest number that’s ever been factored on a gate model system is the number 15 - three times five. The largest number that’s ever been factored on an annealing quantum computer is roughly a 17-bit number. It is basically north of 250,000. So we’re ways away as well, but, you know it’s kind of horse race for, who’s going to be able to factor in 2000 bit semi prime first - annealing or gate model. But all this is really to say that that problem of finding the low energy state in a multidimensional landscape is actually a very broadly applicable problem.

Moderator

Got it. So it sounds like there are problems optimization problems that can be addressed as a satisfiability problem where they can be mapped and run on a quantum annealing system very efficiently as compared to a gate model.

Alan Baratz

Yeah, exactly. Right. And I mean, you, you mentioned machine learning, one of the approaches to machine learning is called probabilistic machine learning, which is basically training something called a restricted Boltman machine. Well, actually training is a restricted Boltman machine getting samples from that, to train that is actually natively one of those, you know, low energy point in a multidimensional landscape problem.

 

-8-


Moderator

Got it. One of the things you mentioned in the presentation was the 99% uptime that you have with, with the Leap service. I think there, there have been some claims thrown at some of your competitors that say their uptime may be far lower than, you know, 99%.

Alan Baratz

What, what do you think the gate model, you know, the best of breed gate model, quantum computers out there, what do you think their up times are? Because it sounds like they may be a lot lower than 99%. You know, I’m not going to speculate on what their up times are. I, I don’t have access to them. I haven’t had an opportunity to try to use them. So, you know, I can’t really speculate. All I’ll say is we know they’re not commercial grade systems. You know, you can look at the pictures and kind of conclude for yourself. But we, we have very, very high reliability on our systems. And in fact, that uptime is a quantum cloud service uptime. We have quantum computers that we’ve run for four years without having to warm up and recalibrate.

Alan Baratz

And, and frankly, that’s not easy to do because the refrigerators that you would buy off the shelf for a superconducting system, they typically build up contaminants need to be warmed up in three months. Right. We have a lot of IP around modifications to those refrigerators to make them run longer, cause to have a commercial system, you know, you can’t be warming them up every three months and taking them offline. And so we’ve run for up to four years without having to warm up a system. So, we really do focus on reliability and availability, both in our quantum computers, as well as in our quantum cloud service.

Moderator

Wanted to ask you a couple questions about the gate model program. You mentioned that you’ve got the first qubits back in the lab. Do you have any preliminary thoughts you might be able to share with the, with the group on, uh, you know, what kind of coherence times you might be looking at and have you been able to implement gates on those qubits and any thoughts on gate fidelities for the, for this qubit design?

Alan Baratz

So the answer is no, in the sense that we’ve just gotten these back and cooled them down. We’re just now starting to take the measurements. And these are the very first of the gate model qubits that we have fabricated. So it’s a little early for me to be talking about exactly where we are with them. What I can tell you is kind of what the industry knows, In order to be able to do full error correction, you need to be in the 20 to a hundred microsecond coherence time. So that’s where we need to get to, and that’s our target, and we’re, you know, working through the process to get there so that we can then start building the error correction for longer life qubit and so on.

Moderator

Great. We’ve had one question from the audience. Are your customers showing any interest in buying a full, complete Advantage systems?

 

-9-


Alan Baratz

So the answer is yes. But, you know, we don’t sell quantum computers. We sell cloud access to the quantum computers. The reason is it’s just a much better business model for us, and it’s a much better model for our customers as well because with cloud access, they’ll always get the latest and greatest technology. We put it in our cloud as soon as it’s available. They always get high availability because we’ve always got multiple systems in the cloud backing one another up. It allows them to get into the quantum game at a lower price point because they don’t have to shovel out all the money to buy a quantum computer just to be able to get started. So it’s better for them. It’s better for us. Now, do we get requests? Yes. Do we entertain those requests? We will entertain those requests if there’s a good reason to entertain the request.

Alan Baratz

For example, if a three letter government agency comes to us and says, Hey, we want to run classified applications on a system in one of our secure facilities. Okay, that’s a good reason. We will entertain that. But generally, our model is not to sell boxes.

Moderator

Understood. Well, it looks like we’re reaching the end of our, our limits. So I just wanted to say Alan and John, thank you very much for joining us at the Needham technology and media conference. Really a pleasure having you and, and we look forward to following this story.

Alan Baratz and John Markovich

Thanks Quinn. It was a pleasure to be here. Thank you, Quinn. Thank you. Thanks everyone. Goodbye. Bye.

 

-10-


Important Information About the Proposed Transaction between D-Wave Systems Inc. (“D-Wave”) and DPCM Capital, Inc. (“DPCM Capital”) and Where to Find It:

A full description of the terms of the transaction between D-Wave and DPCM Capital is provided in a registration statement on Form S-4, as amended, filed with the Securities and Exchange Commission (the “SEC”) by D-Wave Quantum Inc. that includes a preliminary prospectus with respect to the combined company’s securities, to be issued in connection with the transaction and a preliminary proxy statement with respect to the stockholder meeting of DPCM Capital to vote on the transaction. D-Wave Quantum Inc. and DPCM Capital urge investors, stockholders, and other interested persons to read the preliminary proxy statement/ prospectus, as well as other documents filed with the SEC, because these documents contain important information about D-Wave Quantum Inc., DPCM Capital, D-Wave, and the transaction. After the registration statement is declared effective, the definitive proxy statement/prospectus to be included in the registration statement will be mailed to stockholders of DPCM Capital as of a record date to be established for voting on the transaction. Stockholders also may obtain a copy of the registration statement on Form S-4, as amended—including the proxy statement/prospectus and other documents filed with the SEC without charge—by directing a request to: D-Wave Quantum Inc., 3033 Beta Avenue, Burnaby, BC V5G 4M9 Canada, or via email at shareholdercomm@dwavesys.com and DPCM Capital, 382 NE 191 Street, #24148, Miami, Florida 33179, or via email at mward@hstrategies.com. The preliminary and definitive proxy statement/prospectus to be included in the registration statement, once available, can also be obtained, without charge, at the SEC’s website (www.sec.gov).

No Offer or Solicitation

This communication is for informational purposes only and does not constitute an offer or invitation for the sale or purchase of securities, assets, or the business described herein or a commitment to D-Wave Quantum Inc., DPCM Capital, or D-Wave, nor is it a solicitation of any vote, consent, or approval in any jurisdiction pursuant to or in connection with the transaction or otherwise, nor shall there be any sale, issuance, or transfer of securities in any jurisdiction in contravention of applicable law.

Participants in Solicitation

D-Wave Quantum Inc., DPCM Capital, and D-Wave, and their respective directors and executive officers, may be deemed participants in the solicitation of proxies of DPCM Capital’s stockholders in respect of the transaction. Information about the directors and executive officers of DPCM Capital is set forth in DPCM Capital’s filings with the SEC. Information about the directors and executive officers of D-Wave Quantum Inc. and more detailed information regarding the identity of all potential participants, and their direct and indirect interests by security holdings or otherwise, will be set forth in the definitive proxy statement/prospectus for the transaction when available. Additional information regarding the identity of all potential participants in the solicitation of proxies to DPCM Capital’s stockholders in connection with the proposed transaction and other matters to be voted upon at the special meeting, and their direct and indirect interests, by security holdings or otherwise, will be included in the definitive proxy statement/prospectus, when it becomes available.

 

-11-