This paper describes a method for using Grovers algorithm to create a quantum vector database, the database stores embeddings based on Controlled-S gates, which represent a binary numerical value. This value represents the embeddings value. The process of creating meaningful embeddings is handled by a classical computer and the search process is handled by the quantum computer. This search approach might be beneficial for a large enough database, or it could be seen as a very qubit-efficient (super dense) way for storing data on a quantum computer, since the proposed circuit stores many embeddings inside one quantum register simultaneously.

翻译：本文描述了一种利用Grover算法构建量子向量数据库的方法。该数据库基于受控-S门存储嵌入向量，所存储的二进制数值即代表该嵌入向量值。生成有意义的嵌入向量的过程由经典计算机完成，而搜索过程则由量子计算机处理。对于规模足够大的数据库，这种搜索方法可能具有优势；或可视为在量子计算机上存储数据的一种极高量子比特效率（超密集）方式——因为所提出的电路能在单个量子寄存器中同时存储多个嵌入向量。