Research shows “a very great agreement” between quantum annealing and the way the D-Wave system operates. Dwave is is not using a computing model known as “simulated annealing,” which obeys the laws of classical physics (the physics of everyday life) rather than the more elusive properties of quantum physics.
The machine contains 512 superconducting circuits, each a tiny loop of flowing current. These are cooled to almost absolute zero, the company says, so they enter a quantum state where the current flows both clockwise and counterclockwise at the same time. When you feed the machine a task, it uses a set of algorithms to map a calculation across these qubits — and then execute that calculation. Basically, this involves determining the probability that a given set of circuits will emerge in a particular pattern when the temperature inside the system is raised.
Dwave’s system should be able to perform about 500 quantum annealing step algorithms
The D-Wave system is useful, helping to solve what are known as combinatorial optimization problems, which turn up in everything from genome sequence analysis and protein folding to risk analysis. In announcing its use of the D-Wave machine last month, Google said it would use the system to help advance machine learning — i.e. efforts to create computing systems that can learn in much the same way people do.
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