Quantum Computing Demands a Whole New Kind of Programmer
Quantum computers finally seem to be coming of age with promises of “quantum supremacy” by the end of the year. But there’s a problem—very few people know how to work them.
The bold claim of achieving “quantum supremacy” came on the back of Google unveiling a new quantum chip design. The hyperbolic phrase essentially means building a quantum device that can perform a calculation impossible for any conventional computer.
In theory, quantum computers can crush conventional ones at important tasks like factoring large numbers. That’s because unlike normal computers, whose bits can either be represented as 0 or 1, a quantum bit—or “qubit”—can be simultaneously 0 and 1 thanks to a phenomenon known as superposition.
Demonstrating this would require thousands of qubits, though, which is well beyond current capabilities. So instead Google plans to compare the computers’ ability to simulate the behavior of a random arrangement of quantum circuits. They predict it should take 50 qubits to outdo the most powerful supercomputers, a goal they feel they can reach this year.
Clearly the nature of the experiment tips the balance in favor of their chip, but the result would be impressive nonetheless, and could act as a catalyst to spur commercialization of the technology.
This year should also see the first commercial ‘universal’ quantum computing service go live, with IBM giving customers access to one of its quantum computers over the cloud for a fee. Canadian company D-Wave already provides cloud access to one of its machines, but its quantum computers are not universal, as they can only solve certain optimization problems.
But despite this apparent impetus, the technology has a major challenge to overcome. Programming these devices is much harder than programming conventional computers.
For a start, building algorithms for these machines requires a certain level of understanding about the quantum physics that gives qubits their special properties. While you don’t need an advanced physics degree to get your head around it, it is a big departure from traditional computer programming.
Writing in ReadWrite, Dan Rowinski points out, “Writing apps that can be translated into some form of qubit-relatable code may require some very different approaches, since among other things, the underlying logic for digital programs may not translate precisely (or at all) to the quantum-computing realm.”
And while there are a number of quantum simulators that can run on a laptop for those who want to dip their toes in the water, real quantum computers are likely to behave quite differently. “The real challenge is whether you can make your algorithm work on real hardware that has imperfections,” Isaac Chuang, an MIT physicist, told Nature.
Convincing programmers to invest the time necessary to learn these skills is going to be tricky until commercial systems are delivering tangible benefits and securing customers, but that’s going to be tough if there’s no software to run on them.
The companies building these machines recognize this chicken and egg problem, and it is why there is an increasing drive to broaden access to these machines. Before the announcement of the commercial IBMQ service, the company had already released the free Quantum Experience service last year.
Earlier this year, D-Wave open sourced their Qbsolv and Qmasm tools to allow people to start getting to grips with programming its devices, while a pair of Google engineers built a “Quantum Computing Playground” for people to start investigating the basics of the technology. The company plans to provide access to its devices over the cloud just like IBM.
“We don’t just want to build these machines,” Jerry Chow, the manager of IBM’s Experimental Quantum Computing team told Wired. “We want to build a framework that allows people to use them.”
How easy it will be to translate the skills learned in one of these companies’ proprietary quantum computing ecosystems to another also remains to be seen, not least because the technology at the heart of them can be dramatically different. This could be a further stumbling block to developing a solid pool of quantum programmers.
Ultimately, the kinds of large-scale quantum computers powerful enough to be usefully put to work on real-world problems are still some years away, so there’s no need to panic yet. But as the researchers behind Google’s quantum effort note in an article in Nature, this scarcity of programming talent also presents an opportunity for those who move quickly.
“If early quantum-computing devices can offer even a modest increase in computing speed or power, early adopters will reap the rewards,” they write. “Rival companies would face high entry barriers to match the same quality of services and products, because few experts can write quantum algorithms, and businesses need time to tailor new algorithms.”