Curator's Take
AI Commentary
This article tackles a practical blind spot in the emerging quantum‑as‑a‑service market by introducing Quantum Fidelity‑per‑Cost (QFC), a metric that folds execution accuracy, shot count and real‑world pricing into a single score. By benchmarking 14 cloud access points across four providers, the authors show that cost‑aware rankings can diverge sharply from pure fidelity rankings, meaning that users may pick a cheaper but still competitive backend for many workloads. The work arrives just as enterprises are beginning to budget quantum experiments, offering a concrete tool for informed procurement and highlighting how billing models—not only hardware quality—will shape adoption curves. Readers should note that the QFC formulation depends on each provider’s documented pricing scheme, so changes in cloud tariffs could shift the rankings over time.
— Mark Eatherly
Summary
Cloud-accessible quantum computing has made hardware comparison not only a physics benchmark but also a practical purchasing decision. Cost-aware comparison of quantum computers remains underexplored and is difficult to do under the heterogeneous billing models offered by various cloud-based quantum computing providers. This paper makes two main contributions to enable price-aware comparison of quantum computers. First, this work presents a cross-provider measurement study of quantum circuit execution fidelity spanning 14 cloud QPU access-path entries (12 distinct physical QPUs) across four cloud access paths: Amazon Web Services (AWS) cloud, IBM Quantum Runtime (IBM) cloud, IQM Resonance (IQM) cloud, and Oxford Quantum Circuits (OQC) cloud. Second, this work proposes and analyzes a cost-aware score, Quantum Fidelity-per-Cost (QFC), which combines Kullback--Leibler (KL) divergence from an ideal output distribution, shot count, and monetary cost into one possible metric under a documented billing model. The main empirical observation from this work is that cost-aware ranking can differ from purely fidelity-based evaluation of quantum computers, and that users may select different quantum computing backends when they consider price in their selection, as opposed to selection based on fidelity alone. This work shows that the ranking is stable under reweighting of the metric, and that a device's billing model, not its hardware, governs how its score scales with shot count. Reported QFC values change as new machines come online or as providers revise their prices.