Google Researching Quantum Computing Algorithms and Hardware
December 12th, 2009Via: Google Research Blog:
Over the past three years a team at Google has studied how problems such as recognizing an object in an image or learning to make an optimal decision based on example data can be made amenable to solution by quantum algorithms. The algorithms we employ are the quantum adiabatic algorithms discovered by Edward Farhi and collaborators at MIT. These algorithms promise to find higher quality solutions for optimization problems than obtainable with classical solvers.
On the hardware side we are collaborating with D-Wave in Vancouver, Canada. D-Wave develops processors that realize the adiabatic quantum algorithm by magnetically coupling superconducting loops called rf-squid flux qubits. This design realizes what is known as the Ising model which represents the simplest model for an interacting many-body system and it can be manufactured using proven chip fabrication methods. Unfortunately, it is not easy to demonstrate that a multi-qubit system such as the D-Wave chip indeed exhibits the desired quantum behavior and experimental physicists from various institutions are still in the process of characterizing the chip.
Today, at the Neural Information Processing Systems conference (NIPS 2009), we show the progress we have made. We demonstrate a detector that has learned to spot cars by looking at example pictures. It was trained with adiabatic quantum optimization using a D-Wave C4 Chimera chip. There are still many open questions but in our experiments we observed that this detector performs better than those we had trained using classical solvers running on the computers we have in our data centers today. Besides progress in engineering synthetic intelligence we hope that improved mastery of quantum computing will also increase our appreciation for the structure of reality as described by the laws of quantum physics.
