LLM Reasoning 相关度: 5/10

Qute: Towards Quantum-Native Database

Muzhi Chen, Xuanhe Zhou, Wei Zhou, Bangrui Xu, Surui Tang, Guoliang Li, Bingsheng He, Yeye He, Yitong Song, Fan Wu
arXiv: 2602.14699v1 发布: 2026-02-16 更新: 2026-02-16

AI 摘要

Qute提出了一种量子原生数据库,利用量子计算加速数据处理,并优化量子资源利用。

主要贡献

  • 扩展SQL编译为量子电路
  • 混合优化器动态选择执行计划
  • 选择性量子索引
  • 保真度存储

方法论

论文提出了一种量子数据库框架,通过编译优化、混合执行、索引和存储等技术,实现高效的量子数据处理。

原文摘要

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.

标签

量子计算 数据库 量子数据库 SQL

arXiv 分类

cs.DB cs.AI cs.AR