Demonstration of a scaling advantage for a quantum annealer over simulated annealing

ORAL

Abstract

A complete determination of the optimal time-to-solution (TTS) using the D-Wave quantum annealing processors has not been possible to date, preventing definitive conclusions about the presence of a scaling advantage. The main technical obstacle has been the inability to verify an optimal annealing time within the available range. Here we overcome this obstacle and present a class of problem instances for which we observe an optimal annealing time using a D-Wave 2000Q processor. This allows us to perform an optimal TTS benchmarking analysis and perform a comparison to several classical algorithms, including simulated annealing, spin-vector Monte Carlo, and discrete-time simulated quantum annealing. We establish the first example of a scaling advantage for an experimental quantum annealer over simulated annealing, with 95% confidence, over the range of problem sizes that we can test. However, we do not find evidence for a quantum speedup: simulated quantum annealing exhibits the best scaling by a significant margin.

*This work was supported under ARO grant number W911NF-12-1-0523, ARO MURI Grant Nos. W911NF-11-1-0268 and W911NF-15-1-0582, and NSF grant number INSPIRE-1551064. This research used resources from the USC HPCC and the OLCF.

Presenters

  • Tameem Albash

    • Information Sciences Institute
    • Univ of Southern California

Authors

  • Tameem Albash

    • Information Sciences Institute
    • Univ of Southern California
  • Daniel Lidar

    • Physics, University of Southern California
    • Univ of Southern California
    • University of Southern California