A Taxonomy of Real Faults in Hybrid Quantum-Classical Architectures
Avner Bensoussan, Gunel Jahangirova, Mohammad Reza Mousavi
TL;DR
This work introduces the first empirical taxonomy of real faults in Hybrid Quantum-Classical architectures, focusing on NISQ-era variational workflows. The authors mined over 5000 GitHub issues, curated 529 candidates, and labeled 133 faults, augmented by 52 fault insights from expert interviews, then validated the taxonomy through multiple expert studies. The resulting seven top-level categories (Parametrisation, Conceptualisation, API, Optimisation, Quantum Circuit, Measurement, GPU) with 47 sub-categories provide a structured, extensible fault map grounded in real-world practice, enabling targeted testing, fault injection, and automated repair in hybrid quantum software. The work also yields practical guidelines, supports tool-building for QA, and highlights cross-disciplinary considerations between computer science and physics in diagnosing and mitigating faults in hybrid quantum pipelines.
Abstract
With the popularity of Hybrid Quantum-Classical architectures, particularly noisy intermediate-scale quantum (NISQ) architectures, comes the need for quality assurance methods tailored to their specific faults. In this study, we propose a taxonomy of faults in Hybrid Quantum-Classical architectures accompanied by a dataset of real faults in the identified categories. To achieve this, we empirically analysed open-source repositories for fixed faults. We analysed over 5000 closed issues on GitHub and pre-selected 529 of them based on rigorously defined inclusion criteria. We selected 133 faults that we labelled around symptoms and the origin of the faults. We cross-validated the classification and labels assigned to every fault between two of the authors. As a result, we introduced a taxonomy of real faults in Hybrid Quantum-Classical architectures. Subsequently, we validated the taxonomy through interviews conducted with eleven developers. The taxonomy was dynamically updated throughout the cross-validation and interview processes. The final version was validated and discussed through surveys conducted with an independent group of domain experts to ensure its relevance and to gain further insights.
