Why quantum computing companies like D-Wave are using SPACs to IPO

Yet another quantum computing company has gone public via SPAC.

D-Wave completed a planned merger on Monday with DPCM Capital (the latter of which was already listed on the New York Stock Exchange), making the Canada-based firm the third quantum player to go public via a SPAC—that is, a special purpose acquisition company—within the last year. (The other companies? Rigetti and IonQ.)

It’s an interesting trend, but perhaps not a surprising one: According to D-Wave CEO Alan Baratz, the until-recently-obscure financial quirk offers his company—one that’s in a still-budding sector—faster access to capital.

“In some sense SPACs are ideal for a company that has huge potential but is going to take some time to mature,” he tells Fast Company. “With a SPAC, you’re able to tap into the funding sources in the public markets to accelerate your growth and do it based on the future potential.”

A traditional IPO, on the other hand, is “all about today,” he adds.

SPACs can also save companies money (though this point is subject to some debate). “I don’t think all SPACs should be discounted,” says Patrick Moorhead of Moor Insights & Strategy, a consulting firm. “It’s a much less expensive way to go public and takes less time and effort.”

So far, D-Wave’s post-SPAC stock is holding its own. It opened at $9.98 Monday and closed at $11.86 on Thursday. But Rigetti and IonQ haven’t fared as well. Rigetti has seen its shares drop in value by roughly half since its listing on the NASDAQ in March. IonQ’s shares have lost about 40% of their value since its listing in October 2021.

How companies are using quantum services

In the young field of quantum computing, D-Wave has emerged as a major character. Back in 2011, the company became the first to actually sell a quantum computer; it now counts NASA, Google, and Lockheed Martin as customers.

Building and operating a quantum computer is an extraordinary feat of science and engineering. Instead of the bits used in traditional computers (which can be set to zero or one), quantum computers use subatomic particles called qubits, which can represent many values between zero and one, as well as zero and one at the same time (a “superposition”). Qubits can also entangle to represent values in extremely complex problems. In order to take advantage of these properties, the computer has to control the state of the qubits, whose erratic behavior is governed by quantum physics, not regular physics. This is very hard, and usually involves supercooling the qubits to slow their constant spin, then using lasers or electricity to control their state.

D-Wave was able to get to market with a quantum computer because it adopted a unique approach to working with the qubits—one that asks far less of them. “What it’s looking for is the minimum energy level within a qubit, and by finding the minimum energy level, then they’re able to find the most optimized solution to a problem,” says Heather West, research manager at research firm IDC. “And that’s why D-Wave is able to say they have 5,000 to 7,000 qubits in their system versus an IBM, which is still down around 127.”

Even though that approach, called “quantum annealing,” doesn’t try to exert a lot of control over the states of the qubits, it’s still very useful for solving optimization problems—that is, problems where the goal is to find the best solution among a huge number of possibles. An optimization problem might be finding the optimal routes and cargos for a large fleet of delivery trucks, or finding the optimal number of employees to schedule on a given day. It’s a common type of business puzzle, and annealers are especially good at solving them.

“Some of these industries really gravitated toward D-Wave because of those optimization problems, and being able to pull in all sorts of data to find these optimized solutions and solving problems faster was really appealing,” West says.

That application is a good example of the way companies are using quantum services like D-Wave today. They’re looking for problem types where classical computers struggle and quantum computers excel.

“They [D-Wave] are really more of an accelerator,” says Ashish Nadkarni, group VP and general manager at IDC. “We are not at the point where you can completely run all kinds of jobs on a quantum computer.”

But D-Wave’s annealer may eventually be seen as a forerunner to a more robust kind of quantum computing, called “gate model,” in which the quantum computer takes full advantage of the quantum properties of the qubits–their many possible states, their capacity for “superposition,” and the compute power enabled by multiple qubits entangling with each other.

Controlling and leveraging these properties opens the possibility of solving problems that are far beyond the reach of classical supercomputers (and annealers). These are large “probabilistic” problems where the qubits are asked to model huge and complex data sets. It could be modeling all the receptors in the brain to explore how they’ll react to a drug, or a huge array of stock market conditions to predict their effect on the price of a certain commodity.

Realizing that much of the upside and excitement around quantum computing is coming from the possibility to solve such problems, D-Wave announced last year that it had begun building gate-model quantum computers more like the ones built by Google, IBM, and IonQ. D-Wave will need years to develop its gate-model quantum, but Baratz believes offering both annealers and gate-model quantum computing will eventually put his company at an advantage.

“By doing both and being the only company that’s doing both, we’re the only company in the world that will be able to address the full market for quantum, and the full set of use cases,” he says. D-Wave’s customers typically tap into these computing services via a dedicated cloud service.

“We truly are commercial”

Because quantum is considered a nascent technology, many potential customers (such as companies in the financial services and pharmaceutical industries) are experimenting with running certain types of algorithms on quantum systems to look for some advantage over classical computing. But they’re not necessarily paying customers.

Baratz says that it’s the gate-model quantum services that are “nascent” technology, not D-Wave’s annealers, which he says are ready to deliver real value today. He believes the gate-model quantum computers are still as many as seven years away from being able to run general business applications in a way that beats classical computers.

Baratz believes that D-Wave is now challenged to make sure customers differentiate between gate-model computing—which he says could be as many as seven years away from running real business applications—and D-Wave’s quantum annealing service, which is mature and ready to deliver value today. While his gate-model competitors are out telling customers it’s okay to “dip their toes into the water” and experiment, D-Wave must counter that narrative in the marketplace with the message that customers can be doing real optimization work using quantum annealing now.

“We truly are commercial, so when our competitors talk about revenue, they talk about government research grants as revenue, and they talk about national labs and academic institutions as customers,” Baratz says. “When we talk about our customers, we talk about our recently announced deal with MasterCard, or Deloitte or Johnson & Johnson or Volkswagen.”

Baratz says over 65% of D-Wave’s quantum cloud revenue last year came from more than 50 commercial customers, which include over two dozen members of the Forbes Global 2000.

Baratz says D-Wave is now entering a phase in which it can leverage its annealers to start customer relationships.

“We do have a significant head start, but we think now is the time to really make the investment to grow that loyal customer base and get the market share,” Baratz says. “And then, as we bring new generations of annealing to market, it’s just an upsell to more complex applications as we bring gate [model] to market.”