Inter-generational comparison of quantum annealers in solving hard scheduling problems

TL;DR

This study compares four generations of quantum annealers on complex scheduling problems, revealing significant performance improvements and better scaling with hardware upgrades and optimized parameters.

Contribution

It provides an inter-generational performance comparison of quantum annealers and identifies key factors like hardware upgrades and parameter optimization that enhance their efficiency.

Findings

Advantage outperforms older models significantly.

Optimizing ferromagnetic couplings improves both TTS and scaling.

Scaling exponent reduced from 1.01 to 0.173 across generations.

Abstract

We compare the performance of four quantum annealers, the D-Wave Two, 2X, 2000Q, and Advantage in solving an identical ensemble of a parametrized family of scheduling problems. These problems are NP-complete and, in fact, equivalent to vertex coloring problems. They are also practically motivated and closely connected to planning problems from artificial intelligence. We examine factors contributing to the performance differences while separating the contributions from hardware upgrades, support for shorter anneal times, and possible optimization of ferromagnetic couplings. While shorter anneal times can improve the time to solution (TTS) at any given problem size, the scaling of TTS with respect to the problem size worsens for shorter anneal times. In contrast, optimizing the ferromagnetic coupling improves both the absolute TTS and the scaling. There is a statistically significant improvement in performance between D-Wave Two and 2X and from all older generation annealers to Advantage, even when operated under identical anneal time and ferromagnetic couplings. However, the performance improvement from 2X to 2000Q requires the anneal time and ferromagnetic couplings to be optimized. Overall, owing to these inter-generational hardware improvements and optimizations, the scaling exponent reduces from $1.01 \pm 0.01$ on Two to $0.173 \pm 0.009$ on Advantage.