A comment on comparing optimization on D-Wave and IBM quantum processors

TL;DR

This paper critically examines claims of quantum optimization performance, revealing methodological flaws in prior comparisons and demonstrating that simple quantum annealing on D-Wave outperforms IBM's digitized approach.

Contribution

It identifies major methodological issues in previous performance comparisons and provides a direct, reproducible comparison showing D-Wave's quantum annealing surpasses IBM's digitized quantum annealing.

Findings

Simple unoptimized quantum annealing achieves higher success probabilities.

D-Wave's analog quantum annealing reaches lower energies than IBM's digitized method.

Reproducible results contradict prior claims of IBM's superior performance.

Abstract

Recent work [Sachdeva et al.] presented an iterative hybrid quantum variational optimization algorithm designed by Q-CTRL and executed on IBM gate-based quantum processing units (QPUs), claiming a significant performance advantage against a D-Wave quantum annealer. Here we point out major methodological problems with this comparison. Using a simple unoptimized workflow for quantum annealing, we show success probabilities multiple orders of magnitude higher than those reported by [Sachdeva et al.]. These results, which can be reproduced using open-source code and free trial access to a D-Wave quantum annealer, contradict Q-CTRL's claims of superior performance. We also provide a direct comparison between quantum annealing and a recent demonstration of digitized quantum annealing on an IBM processor, showing that analog quantum annealing on a D-Wave QPU reaches far lower energies than digitized quantum annealing on an IBM QPU.