标题： 基于电路的量子随机存取存储器用于经典数据 显示英文标题

标题： Circuit-Based Quantum Random Access Memory for Classical Data

摘要： 许多量子信息处理任务要真正超越经典方法，需要一种高效的将经典数据编码为量子叠加态的程序。 在本工作中，我们提出一种基于电路的翻转-锁存量子随机存取存储器，以系统且灵活的方式构建经典信息的量子数据库。 对于由$M$个条目组成的经典数据，每个条目由$n$位表示，该方法需要$O(n)$个量子比特和$O(Mn)$步骤。 通过额外的成本进行后选择，我们的方法还可以将连续数据存储为概率幅。 作为一个例子，我们提出一种将量子监督学习算法的经典训练数据转换为量子态的程序。 通过引入量子分叉，可以进一步减少状态准备查询的数量来提高性能。 显示英文摘要

摘要： A prerequisite for many quantum information processing tasks to truly surpass classical approaches is an efficient procedure to encode classical data in quantum superposition states. In this work, we present a circuit-based flip-flop quantum random access memory to construct a quantum database of classical information in a systematic and flexible way. For registering or updating classical data consisting of $M$ entries, each represented by $n$ bits, the method requires $O(n)$ qubits and $O(Mn)$ steps. With post-selection at an additional cost, our method can also store continuous data as probability amplitudes. As an example, we present a procedure to convert classical training data for a quantum supervised learning algorithm to a quantum state. Further improvements can be achieved by reducing the number of state preparation queries with the introduction of quantum forking.