Using Superconducting Quantum
Computers to Solve Artificial
Intelligence Problems: Preliminary
Results
September 13, 2007
10:00 AM
ORNL, 5100-Auditorium
Host: Jeffrey Vetter
(vetter@ornl.gov
)
ABSTRACT:
D-Wave processors are designed to
harness a fundamental principle of nature that operates in both quantum and
classical regimes—the propensity for all physical systems to minimize their free
energy. The computational model underlying this design is referred to as quantum
annealing, which is a novel heuristic approach to solving optimization problems.
The long-time limit of quantum annealing is known as adiabatic quantum
computation, which is a universal model for quantum computation. In this seminar
I will introduce this computational model and provide some context for why we
are focusing on it. I will then introduce our hardware, which is based on
lithographically defined niobium circuits, and present results of some device-
and processor-level testing. Finally I’ll describe how such hardware can be used
in a hybrid quantum/classical heuristic algorithm for Maximum Common Subgraph, a
problem that arises in several artificial intelligence
problems.
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