Distinguishing Quantum Software Bugs from Hardware Noise: A Statistical Approach

Files

2507.20475v1.pdf (809.27 KB)

Links to Files

http://arxiv.org/abs/2507.20475

Permanent Link

https://doi.org/10.48550/arXiv.2507.20475
 http://hdl.handle.net/11603/39795

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UMBC Faculty Collection
UMBC Information Systems Department

Author/Creator

Author/Creator ORCID

https://orcid.org/0000-0001-9343-3654

Date

2025-07-28

Type of Work

conference papers and proceedings
postprints
Text

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Program

Citation of Original Publication

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This item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.

Subjects

Quantum Physics
Computer Science - Software Engineering

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.