Distinguishing Quantum Software Bugs from Hardware Noise: A Statistical Approach
Abstract
Quantum computing in the Noisy Intermediate-Scale Quantum (NISQ) era presents significant challenges in differentiating quantum software bugs from hardware noise. Traditional debugging techniques from classical software engineering cannot directly resolve this issue due to the inherently stochastic nature of quantum computation mixed with noises from NISQ computers. To address this gap, we propose a statistical approach leveraging probabilistic metrics to differentiate between quantum software bugs and hardware noise. We evaluate our methodology empirically using well-known quantum algorithms, including Grover's algorithm, Deutsch-Jozsa algorithm, and Simon's algorithm. Experimental results demonstrate the efficacy and practical applicability of our approach, providing quantum software developers with a reliable analytical tool to identify and classify unexpected behavior in quantum programs.
Keywords
Cite
@article{arxiv.2507.20475,
title = {Distinguishing Quantum Software Bugs from Hardware Noise: A Statistical Approach},
author = {Ahmik Virani and Devraj and Anirudh Suresh and Lei Zhang and M V Panduranga Rao},
journal= {arXiv preprint arXiv:2507.20475},
year = {2025}
}
Comments
12 pages, 30 figures, accepted by the IEEE International Conference on Quantum Computing and Engineering (QCE), IEEE Quantum Week, 2025