(HPCWire) Researchers at the Oak Ridge Leadership Computing Facility (OLCF) and University of Tennessee, Knoxville (UTK) established a quantum annealing benchmark for optimization problems with the help of a quantum computer.
The OLCF is a US Department of Energy (DOE) Office of Science User Facility at Oak Ridge National Laboratory (ORNL).
To set the benchmark, the team used a problem called portfolio optimization as a case study. In this problem, investors attempt to choose a combination of financial stocks that provide maximum gains while minimizing risk, said Erica Grant, coauthor of the study and doctoral candidate in energy science and engineering at the Bredesen Center for Interdisciplinary Research and Graduate Education at UTK.
“There are a lot of different combinations of assets that you can choose to invest in, each with its own risks and rewards. And because there are so many different options, a classical computer needs to find some way of filtering through them, something that can take a lot of time, which is why using classical supercomputers for this type of problem is not a computationally efficient option,” said Grant, who worked with Travis Humble, deputy director of the DOE Quantum Science Center and head of the OLCF’s Quantum User Program.
To find an alternative path, OLCF researchers used the D-Wave 2000Q Quantum Annealer. The machine, designed by Canada-based D-Wave Systems Inc., relies on the power of 2,000 qubits to solve instances of portfolio optimization via quantum annealing.