AbuGhanem Muhammad
Faculty of Science, Ain Shams University, Cairo, 11566, Egypt.
Sci Rep. 2025 Jan 8;15(1):1281. doi: 10.1038/s41598-024-80188-6.
Quantum computing is on the cusp of transforming the way we tackle complex problems, and the Grover search algorithm exemplifying its potential to revolutionize the search for unstructured large datasets, offering remarkable speedups over classical methods. 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 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.
量子计算正处于改变我们处理复杂问题方式的边缘，而格罗弗搜索算法体现了其在革新对非结构化大型数据集搜索方面的潜力，与经典方法相比能显著加速。在此，我们报告了使用超导量子架构的先进可扩展量子计算技术实现并表征三量子比特格罗弗搜索算法的结果。为深入研究该算法的可扩展性和性能指标，我们的研究涵盖了在IBM量子公司的127量子比特量子计算机上，针对所有八个可想象的单结果预言机以及九个双结果预言机执行该算法。此外，我们进行了五次量子态层析成像实验，以精确测量我们所实现算法在从有噪声、无噪声环境到现实世界量子硬件复杂性等不同条件下的行为和效率。通过将理论概念与现实世界实验相联系，本研究不仅揭示了有噪声的中规模量子计算机在促进大规模数据库搜索方面的潜力，还为格罗弗搜索算法在现实世界量子计算应用中的实际应用提供了宝贵见解。
