To make a business case for quantum computing that justifies the risk of investment, first understand what quantum computing is and then define hardware and software options and metrics for success.
Some players are racing to reach quantum supremacy, when a quantum computer is used to solve a theoretical problem that a classical computer cannot, according to Brian Hopkins, VP and principal analyst at Forrester, in an interview with CIO Dive. But first they need a quantum computer.
There are two general classes of quantum computers, according to Hopkins:
Scalable, universal computers: Understand and execute logic like a classical computer, error-corrected, can solve a lot of problems without having to be specialized
Specialized computers: Use quantum annealing for domain-specific optimization problems
Error correction produces stable, fault-tolerant qubits and is a crucial component for universal computers because physical qubits destabilize quickly, though experts generally agree such a computer is at least a decade away. Specialized computers look to get around the demands of error correction, Hopkins said.
Some questions persist on whether the industry can reach error-corrected technology. Right now researchers can error correct a handful of qubits, but the type of quantum computing that would be used to break something like encryption schemes could require thousands, if not millions, he said.
Microsoft, Intel and Google are working on universal, scalable quantum computers. Microsoft is a "dark horse" in the space, according to Hopkins, hinging its bets on topological qubits that it believes will achieve error correction before IBM or Google.
But Microsoft has yet to produce a working quantum computer, and until it has one with a few qubits, the scaling challenge has to wait.
Intel has been working on two kinds of qubits: superconducting and spin qubits, and the latter appears more likely to scale to larger numbers in the long term, according to Jim Clarke, director of quantum hardware at Intel, in an interview with CIO Dive.
The company will eventually settle on one type of qubit — though perhaps a different one than it is working on now, depending on if a more promising alternative arises.
Teamwork makes the dream work
Just like blockchain, quantum technology is surrounded by a lot of hype, which can work to the detriment of the technology's development.
With the hope that a pot of gold waits around the corner for whoever finds it first, companies have been focusing more on internal work than industrywide collaboration, according to Clarke. But anything at least a decade out from fruition should beget more teamwork.
In the current environment, collaboration is "probably not happening to the extent that it needs to happen, perhaps to the extent that the progression of quantum computing would be a little bit slower than if there was wide collaboration among industry and academia," Clarke said.
And with companies working on different architectures and qubits, finding common ground can also be a challenge.
Focusing on higher architectures or on common challenges and applications could help industry, academia and government overcome the gaps — because it would be a missed opportunity not to collaborate more in the coming years, he said.
In June, the National Quantum Initiative Act was introduced in the Senate and laid out plans for a federal program to accelerate and coordinate quantum research and development, especially through interagency and public-private partnerships.
The act could help the U.S. stay ahead of the global quantum race, though it will be important for money to be dispersed on a project or grander theme basis and not to individual researchers or organizations, Clarke said.
Bringing more talent into the field to innovate is also crucial. There is some misperception that to work in quantum one needs quantum expertise. In reality, a lot of the researchers are materials experts, device physicists, patterning experts or system architects, according to Clarke.
There are quantum experts too, but not enough are coming out of universities to fill industry need — a common problem across technology domains.
When supremacy is reached, it won't be universal for all quantum computers. Indeed, very few companies will be able to produce a quantum computer because of the monetary, resource and talent demands.
Cloud-based models will help make the technology accessible to researchers without hardware access. IBM is the first company offering quantum computing capabilities in the cloud, and members of the IBM Q Network can get access to the hardware, software and expertise to grow their own projects.
Cloud-based quantum computing capabilities will be an important conduit for the quantum software market, the widest opportunity area in the field.
Quantum software will follow the model of traditional software with domain-specific solutions and algorithms, and some fields are emerging as frontrunners.
Thus far, most IBM partners have fallen into the fields of material science or chemistry and banking and financial services, said Jeffrey Welser, VP and lab director at IBM Research, in an interview with CIO Dive. Material science and chemistry are expected to be one of the first quantum applications with tangible value.
JSR Corporation has been working with IBM Q Experience since last year because the company believes quantum chemistry can overcome a deficiency in classical computing to generate highly accurate molecule calculations, according to Yuuya Oonishi, a researcher of JSR, in a statement emailed to CIO Dive.
But starting a quantum computing project isn't plug and play.
JSR has most benefited from knowledge transfer in the partnership, such as face-to-face lectures from researchers, prototype codes to calculate molecules and an in-house researcher assigned to IBM Q's Keio Hub. While the company has not yet used the technology for business because the algorithms are not established enough, it is accelerating computing time and model size, Oonishi said.
And by staying abreast of the improvement and growth in the field, JSR gets the latest information to decide what parts of the technology will be useful to them.
Quantum chemistry applications are especially promising because it is easier to make a clear business case for what the technology will offer to justify the risk of investment. For example, companies that produce electric car batteries could use quantum chemistry to figure out a different battery composition that has similar performance to a company like Tesla, which relies on expensive elements, according to Hopkins.