Google Test Has Confirmed D-Wave Quantum Computers are Actually Working, and it Could Mean Major Advances are Near

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Researchers at Google’s Quantum AI Lab have confirmed the D-Wave quantum machine that it and NASA have been testing for two years has beaten a conventional computer in a series of tests.

Google's Quantum Artificial Intelligence Lab has announced that it has confirmed that their D-Wave quantum computer is much faster than simulated annealing — a simulation of quantum computation on a classical computer chip.  According to one writer, "If confirmed, this discovery could not only lead to iRobot-style artificial intelligence but also advance the US space program by light years."

"We found that for problem instances involving nearly 1000 binary variables, quantum annealing significantly outperforms its classical counterpart, simulated annealing."

Google and NASA partnered to set up the D-Wave test machine in 2013, sharing the purchase and hosting of the machine from the Canadian company.

"We found that for problem instances involving nearly 1000 binary variables, quantum annealing significantly outperforms its classical counterpart, simulated annealing," writes Hartmut Neven, Google Director of Engineering of the quantum hardware group on a company blog.

The team also compared the quantum hardware to another algorithm called Quantum Monte Carlo. This method is designed to emulate the behavior of quantum systems, but it runs on conventional processors.

Results of the research have been published in a paper available online.

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"While the scaling with size between these two methods is comparable, they are again separated by a large factor sometimes as high as 10⁸," write the researchers.

So far, algorithmic simulations of the quantum annealing processes have been much more effective than the first generation complicated D-Wave technology, but it is progressing at faster-than-exponential rates.

"Due to the denser connectivity of next generation annealers, we expect those methods will become ineffective," states Neven.

In our experience we find that lean stochastic local search techniques such as simulated annealing are often the most competitive for hard problems with little structure to exploit. Therefore, we regard simulated annealing as a generic classical competition that quantum annealing needs to beat. We are optimistic that the significant runtime gains we have found will carry over to commercially relevant problems as they occur in tasks relevant to machine intelligence.

More work is needed to turn existing quantum systems like D-Waves into a practical technology, conclude the researchers. "The design of next generation annealers must facilitate the embedding of
problems of practical relevance."

They would specifically like to increase the density and control precision of the connections between the qubits as well as their coherence as well as enhance the representation of quadratic optimization and other higher order optimization scenarios. Researchers at D-Wave and other projects, including other quantum computer projects at Google, are working on systems with larger and larger sets of qubits to meet these demands.

SOURCE  Google Research

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