Quantum Optimization of Fully-Connected Spin Glasses

TL;DR

This paper investigates the performance of a quantum annealer in optimizing fully-connected spin glasses, comparing it to simulated annealing, and analyzes how noise and embedding parameters affect outcomes.

Contribution

It demonstrates the correlation between quantum annealer performance and simulated annealing, and links optimal embedding parameters to the spin-glass critical temperature.

Findings

Quantum annealer performance correlates with simulated annealing results.

Static noise impacts the comparative scaling of the two methods.

Optimal embedding parameters relate to the spin-glass critical temperature.

Abstract

The Sherrington-Kirkpatrick model with random $\pm1$ couplings is programmed on the D-Wave Two annealer featuring 509 qubits interacting on a Chimera-type graph. The performance of the optimizer compares and correlates to simulated annealing. When considering the effect of the static noise, which degrades the performance of the annealer, one can estimate an improvement on the comparative scaling of the two methods in favor of the D-Wave machine. The optimal choice of parameters of the embedding on the Chimera graph is shown to be associated to the emergence of the spin-glass critical temperature of the embedded problem.