Quantum Testing and Validation

Jiaming Ye, Xiongfei Wu, Shangzhou Xia +2 more

As quantum computing continues to emerge, ensuring the quality of quantum programs has become increasingly critical. Quantum program testing has emerged as a prominent research area within the scope of quantum software engineering. While numerous approaches have been proposed to address quantum program quality assurance, our analysis reveals that most existing methods rely on measurement-based validation in practice. However, due to the inherently probabilistic nature of quantum programs, measurement-based validation methods face significant limitations.To investigate these limitations, we conducted an empirical study of recent research on quantum program testing, analyzing measurement-based validation methods in the literature. Our analysis categorizes existing measurement-based validation methods into two groups: distribution-level validation and output-value-level validation. We then compare measurement-based validation with statevector-based validation methods to evaluate their pros and cons. Our findings demonstrate that measurement-based validation is suitable for straightforward assessments, such as verifying the existence of specific output values, while statevector-based validation proves more effective for complicated tasks such as assessing the program behaviors.

Anonymous

Emma Andrews, Aruna Jayasena, Prabhat Mishra

Quantum computing has the potential to solve a wide variety of classically intractable problems. However, the inherent complexity, probabilistic behavior, and fragility of quantum systems pose significant challenges to ensuring the correctness and reliability of quantum programs. In this survey, we present a comprehensive overview of functional testing and validation techniques aimed at addressing these challenges for quantum circuits. We begin by outlining the unique characteristics of quantum systems that complicate traditional testing methodologies, including the absence of classical oracles, non-determinism due to quantum measurement, and the exponential growth of the state space. We then categorize and analyze a wide range of functional testing and validation techniques that have emerged to meet these challenges, including mutation testing, fuzz testing, and coverage testing. We further explore advanced semantic and white-box methods such as property-based testing, metamorphic testing, equivalence checking, fault testing, assertions, and concolic testing. Specifically, we discuss the applicability of these testing techniques to quantum circuits and examine their limitations in the current NISQ (Noisy Intermediate-Scale Quantum) era.

Macario Polo

Alexander S. Dellios, M. D. Reid, P. D. Drummond

Abstract An important challenge with the current generation of noisy, large-scale quantum computers is the question of validation. Does the hardware generate correct answers? If not, what are the errors? This issue is often combined with questions of computational advantage, but it is a fundamentally distinct issue. In current experiments, complete validation of the output statistics is generally not possible because it is exponentially hard to do so. Here, we apply phase-space simulation methods to partially verify recent experiments on Gaussian boson sampling (GBS) implementing photon-number resolving detectors. The positive-P phase-space distribution is employed, as it uses probabilistic sampling to reduce complexity. It is ∼ 10 18 times faster than direct classical simulation for experiments on 288 modes where quantum computational advantage is claimed. When combined with binning and marginalization to improve statistics, multiple validation tests are efficiently computable, of which some tests can be carried out on experimental data. We show that the data as a whole has discrepancies with theoretical predictions for perfect squeezing. However, a modification of the GBS parameters greatly improves agreement for some tests. We suggest that such validation tests could form the basis of feedback methods to improve GBS experiments.