Google has published a research paper claiming that D-Wave quantum computers have proven to be much faster at solving some problems than standard computers running a comparable algorithm. In fact, it is more than 100 million times faster, the firm states.
Google purchased a quantum computer from D-Wave Systems two years ago, stating that it was to install the system at the newly formed Quantum Artificial Intelligence Lab, set up as a collaborative project between Nasa, Google and the Universities Space Research Association (USRA) to look into the potential of quantum computing to advance machine learning.
Now, Google has announced test results that appear to show that the D-Wave computer is capable of significantly outperforming a standard computer in two use cases; one involving a process called quantum annealing and another using a quantum version of Monte Carlo simulation.
Hartmut Neven, director of Engineering at Google, detailed the results in a posting on the Google Research Blog.
"We found that for problem instances involving nearly 1,000 binary variables, quantum annealing significantly outperforms its classical counterpart, simulated annealing. It is more than 108 times faster than simulated annealing running on a single core," he wrote.
"We also compared the quantum hardware to another algorithm called Quantum Monte Carlo. This is a method designed to emulate the behaviour of quantum systems, but it runs on conventional processors. While the scaling with size between these two methods is comparable, they are again separated by a large factor sometimes as high as 108," he added.
D-Wave's technology has been the subject of some controversy, as it uses a different approach to quantum computing than many other systems that are still little more than research projects. Some sceptics had even questioned whether D-Wave's computers actually truly exploit quantum effects to produce their results.
Google's results show that the D-Wave in question, a D-Wave 2X unit, is much faster than a classical computer for the specific problems it was tested against.
However, Neven conceded that while the results are "intriguing and very encouraging", there is still much more work that needs to be done to develop "quantum-enhanced optimisation" into a practical technology.
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