Further Reading A detour into the strange world of quantum computing

Quantum computing promises a huge speedup for certain classes of problems, such as factoring numbers into primes. But so far, building a true quantum computer with more than a few bits of processing power has proven an insurmountable hurdle. A company called DWave initially confused matters by announcing that it had developed a quantum computer, but after a bit of back-and-forth, the company has settled on calling its machine a quantum optimizer. It can perform calculations that may rely on quantum effects, but it's not a general quantum computer.

With that settled, the obvious question became whether the quantum optimizer was worth the money—did it actually outperform classical computers for some problems? Some initial results published last year looked promising, as an early production machine outperformed classical computers on a number of tests. But that work came under fire because some of the algorithms run on the classical machine weren't as optimized as they could have been.

Now, a new team of computer scientists has taken DWave's latest creation, a 512-bit quantum optimizer, and put it through its paces on a single problem. And here, the results are pretty clear: a single classical processor handily beats the DWave machine in most circumstances.

The work was done by a large team that includes people from where the DWave 2 machine is housed (USC), a lone Google employee, and a handful of researchers from other academic institutions. The USC machine is an updated version of the one that ran the previous set of tests; 503 of its bits are functional, making it significantly more powerful than the previous version. In this case, rather than tackling a variety of problems, the team focused on a single one: resolving what's called a "spin glass," which starts with a collection of individual spins that are randomly oriented and then finds a low-energy state as those spins interact and reorient.

In theory, this is similar to how the DWave machine works, so (at least in a superficial analysis) you might expect the machine to perform well on the problem. To get its answer, it simply simulates the same process rather than taking an algorithmic shortcut.

Pitted against it is a single-processor classical computer.

You'd think that simulating a process would be rather inefficient compared to actually running a similar process. But you'd be wrong. If you only consider the time involved in performing the calculations, then DWave does show a considerable advantage, one that starts off rising as the complexity of the problem increases. But at some point, that trend reverses. By the time the problem size is approaching that of the number of bits in DWave's machine, the gains have largely vanished.

And that's only considering the time spent calculating. The DWave machine needs time to be set up to model the problem, and then it needs to expend time on error correction. When the full time involved in performing the calculation is considered, the classical computer outperforms the DWave machine on most problems, often by a wide margin. "We find that while the DW2 is sometimes up to 10× faster in pure annealing time," the authors say, "there are many cases where it is ≥ 100× slower."

The researchers readily admit that spin glass isn't the only problem that the DWave machine can solve, and there may be others that it handles better. It's also possible, they recognize, that better error correction could give DWave's quantum optimizer a boost. But it could also be that the optimizer just isn't as good as a classical computer (though a better implementation of this optimization might be).

We may not have to wait too long to find out, as the authors say, "Future studies will probe these alternatives and aim to determine whether one can find a class of problem instances for which an unambiguous speedup over classical hardware can be observed."

The arXiv. Abstract number: 1401.2910 (About the arXiv).