The Grover search algorithm is a pivotal advancement in quantum computing,
promising a remarkable speedup over classical algorithms in searching
unstructured large databases. Here, we report results for the implementation
and characterization of a three-qubit Grover search algorithm using the
state-of-the-art scalable quantum computing technology of superconducting
quantum architectures. To delve into the algorithm's scalability and
performance metrics, our investigation spans the execution of the algorithm
across all eight conceivable single-result oracles, alongside nine two-result
oracles, employing IBM Quantum's 127-qubit quantum computers. Moreover, we
conduct five quantum state tomography experiments to precisely gauge the
behavior and efficiency of our implemented algorithm under diverse conditions;
ranging from noisy, noise-free environments to the complexities of real-world
quantum hardware. By connecting theoretical concepts with real-world
experiments, this study not only shed light on the potential of NISQ (Noisy
Intermediate-Scale Quantum) computers in facilitating large-scale database
searches but also offer valuable insights into the practical application of the
Grover search algorithm in real-world quantum computing applications.

使用超导量子架构的先进量子计算技术，对三比特 Grover 搜索算法进行了实现和特性研究，并通过实验评估了算法的可扩展性和性能指标，同时还进行了量子态重构实验，揭示 NISQ 计算机在大规模数据库搜索方面的潜力及 Grover 搜索算法在实际量子计算应用中的应用价值。