Abstract

Quantum annealing is a proposed combinatorial optimization technique meant to exploit quantum mechanical effects such as tunneling and entanglement. Real-world quantum annealing-based solvers require a combination of annealing and classical pre- and post-processing; at this early stage, little is known about how to partition and optimize the processing. This article presents an experimental case study of quantum annealing and some of the factors involved in real-world solvers, using a 504-qubit D-Wave Two machine and the graph isomorphism problem. To illustrate the role of classical pre-processing, a compact Hamiltonian is presented that enables a reduced Ising model for each problem instance. On random N-vertex graphs, the median number of variables is reduced from N2 to fewer than N log2N and solvable graph sizes increase from N = 5 to N = 13. Additionally, error correction via classical …

Date

June 8, 2015

Authors

Kenneth M Zick, Omar Shehab, Matthew French

Journal

Scientific reports

Volume

5

Issue

1

Pages

11168

Publisher

Nature Publishing Group UK