(PhysicsToday) John Preskill of Caltech, a leading theorist in the quantum computing field field, says that over the past couple of years he has observed a shift in expectations about commercialization that is “reflected in a ramping up by tech companies and venture capital.” Still, he cautions, “nobody knows when we will have applications running on quantum platforms. I am concerned that the expectations may be inflated as far as time scale.”
Milestones leading to the shift in attitude include the first commercial quantum computers, marketed in 2015 by the Canadian company D-Wave, and the first publicly accessible cloud-based quantum computer, introduced in 2016 by IBM.
In October 2019, to great fanfare, Google demonstrated quantum supremacy by performing a calculation deemed impractical or impossible for a classical computer: With 53 quantum bits, or qubits, it solved a math problem in 200 seconds that would have taken much longer on a high-performance computer.
Still, hurdles remain to achieving useful quantum computers. The number of qubits needs to be scaled up. The qubits are needed not only for computations but also for correcting errors due to decoherence of the fragile quantum state. Engineering infrastructure must be designed and built. Algorithms must be created.
The last few years have seen the debut of quantum computers of increasing size and power. “It’s getting to the stage where quantum computing is not yet useful,” notes Martinis, “but it’s useful for research on quantum computing, and that is in itself really interesting.”
Possible initial applications that many researchers anticipate are in quantum chemistry and materials science. Simulations with quantum computers could lead to more efficient batteries and molecules deployed for cleaning the environment.
In the meantime, many researchers are looking for possible applications with current systems. In the noisy intermediate-scale quantum (NISQ) computing regime, the idea is to write algorithms with few gate operations so they can run before the system is overwhelmed by decoherence. “NISQ is what we do before we can do error correction,” says Duke University physicist and IonQ cofounder Jungsang Kim.
A possible dark horse in the race to useful quantum computers is the five-year-old Palo Alto–based PsiQuantum, which takes a photonics approach to qubits. The company is leapfrogging NISQ and aiming directly for error correction.
Companies, university researchers, and governments are entering the quantum computing arena. China, Japan, and other countries are investing in quantum computing. In December 2018 President Trump signed into law the National Quantum Initiative, which, among other things, set a 10-year plan for the field.
A growing number of companies are offering quantum computing via the cloud—so far, in addition to IBM, the list includes Microsoft, Honeywell, Alpine Quantum, D-Wave, Rigetti Computing, QuEra, and Atom Computing.
“The field is making good progress,” says Martinis. “It’s a mixture of well-placed optimism and a bit of hype.”
For now, though, with the range of components available, “It’s like during the Gold Rush: The ones benefiting are the shovel makers.”

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