New Scientist reports that Matthias Troyer of ETH Zurich in Switzerland has tested a D-Wave Two computer against a conventional, “classical” machine running an optimised algorithm – and they have found no evidence of superior performance in the D-Wave machine.
DWave, Google and Lockheed remain optimistic of the usefulness of the machine and of future speed up.
Troyer’s team ran their tests on a D-Wave Two owned by Lockheed Martin and operated by the University of Southern California in Los Angeles. There were certain instances in which the D-Wave computer was up to 10 times faster at problem solving, but in other instances it was one-hundredth the speed of the classical computer. D-Wave’s advantage also tended to disappear when the team added in the time needed to configure the D-Wave Two to solve the problem, a step that is not necessary on regular PCs.
Entanglement lies at the core of quantum algorithms designed to solve problems that are intractable by classical approaches. One such algorithm, quantum annealing (QA), provides a promising path to a practical quantum processor. We have built a series of scalable QA processors consisting of networks of manufactured interacting spins (qubits). Here, we use qubit tunneling spectroscopy to measure the energy eigenspectrum of two- and eight-qubit systems within one such processor, demonstrating quantum coherence in these systems. We present experimental evidence that, during a critical portion of QA, the qubits become entangled and that entanglement persists even as these systems reach equilibrium with a thermal environment. Our results provide an encouraging sign that QA is a viable technology for large-scale quantum computing.
Scott Aaronson has written his take and has announced his “second retirement” as “chief Dwave Critic However, I am expecting this to be like Michael Corleone. Michael Corleone: Just when I thought I was out… they pull me back in.
The findings don’t worry Google: “At this stage we’re mainly interested in understanding better what limits and what enhances the performance of quantum hardware to inform future hardware designs,” says Google spokesman Jason Freidenfelds. He says Google is also more focused on problems with different structures than the one used in Troyer’s test, such as machine-learning problems like the Glass blink-detection algorithm.
Google had also used the machine to help improve machine learning of automatic classification of images. They were able to improve the identification of cars in pictures. This work is applicable to the self driving car work.
Even as they continue to test out the hardware, teams at NASA are developing algorithms for D-Wave to help with astrophysics, including the hunt for exoplanets. At an astronomy meeting last week, NASA contractor Randall Correll of RRC Research in Arlington, Virginia, presented the results of tests run on data from the Kepler mission, which spent four years looking for planets that cross in front of their stars, from Earth’s perspective. These transits create a tiny, regular dip in starlight that reveals an orbiting planet. The bigger the world or the dimmer the star, the more noticeable the dip.
Combing the Kepler data has so far resulted in the discovery of 238 planets and thousands more candidates, most of them either bigger than Earth or orbiting stars smaller than the sun. But Kepler should have been able to spot Earth-sized planets around bright, sun-like stars too.
Correll’s team hopes that quantum processing can dig deeper into the Kepler data and pick out these worlds buried in the background noise. So far their D-Wave algorithm can match current efforts and identify known Kepler worlds, but they have not been able to find any new planets hidden in the data.
Troyer’s study notes that this kind of research on other problem types could help answer whether D-Wave’s computers are faster than PCs. And a more definitive answer may arrive later this year, as D-Wave is scheduled to release a new version of its quantum chip, this time with 1000 qubits.
But critics argue that the latest work is already a sign of defeat. “Bottom line: I think it’s consistent with the picture that’s been emerging of no good evidence for better scaling behaviour,” says Scott Aaronson of the Massachusetts Institute of Technology. “I see no reason why simply increasing from 500 to 1000 qubits should be expected to change anything.”
D-Wave remains optimistic about its machine’s potential. “Our customers are interested in solving real-world problems that classical computers are less suited for and are often more complex than what we glean from a straightforward benchmarking test,” says D-Wave’s Jeremy Hilton. He adds that D-Wave’s upcoming 1000-qubit processor should improve benchmark results and that the company expect to surpass state-of-the-art traditional computers in the next few years. “We haven’t yet seen any fundamental limits to performance that cannot be improved with design changes.”
Brian Wang is a Futurist Thought Leader and a popular Science blogger with 1 million readers per month. His blog Nextbigfuture.com is ranked #1 Science News Blog. It covers many disruptive technology and trends including Space, Robotics, Artificial Intelligence, Medicine, Anti-aging Biotechnology, and Nanotechnology.
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