This paper envisions a quantum database (Qute) that treats quantum computation as a first-class execution option. Unlike prior simulation-based methods that either run quantum algorithms on classical machines or adapt existing databases for quantum simulation, Qute instead (i) compiles an extended form of SQL into gate-efficient quantum circuits, (ii) employs a hybrid optimizer to dynamically select between quantum and classical execution plans, (iii) introduces selective quantum indexing, and (iv) designs fidelity-preserving storage to mitigate current qubit constraints. We also present a three-stage evolution roadmap toward quantum-native database. Finally, by deploying Qute on a real quantum processor (origin_wukong), we show that it outperforms a classical baseline at scale, and we release an open-source prototype at https://github.com/weAIDB/Qute.

翻译：本文提出了一种量子数据库（Qute），将量子计算视为一等执行选项。与先前基于模拟的方法不同——这些方法要么在经典机器上运行量子算法，要么将现有数据库适配用于量子模拟——Qute则（i）将一种扩展形式的SQL编译为门高效的量子电路，（ii）采用混合优化器动态选择量子与经典执行计划，（iii）引入选择性量子索引，以及（iv）设计保真度存储以缓解当前量子比特的限制。我们还提出了实现量子原生数据库的三阶段演进路线图。最后，通过在真实量子处理器（origin_wukong）上部署Qute，我们证明其在大规模场景下优于经典基线，并在https://github.com/weAIDB/Qute发布了开源原型。