论文标题
用于量子状态准备的分界线和诱导算法
A divide-and-conquer algorithm for quantum state preparation
论文作者
论文摘要
随着量子计算机的兴起，预计几个研究和工业领域的优势。但是，在量子计算机中加载经典数据的计算成本可以对可能的量子加速施加限制。创建任意量子状态的已知算法需要具有深度O（n）的量子电路以加载N维矢量。在这里，我们表明，可以在辅助量子尺寸中加载具有量子载体深度和纠缠信息的量子电路的n维矢量。结果表明，我们可以使用划分和串用策略在量子设备中有效加载数据，以交换空间的计算时间。我们在真实的量子设备上展示了概念证明，并为量子机学习提供了两个应用程序。我们希望这种新的加载策略可以允许任务的量子加速，这些任务需要将大量信息加载到量子设备上。
Advantages in several fields of research and industry are expected with the rise of quantum computers. However, the computational cost to load classical data in quantum computers can impose restrictions on possible quantum speedups. Known algorithms to create arbitrary quantum states require quantum circuits with depth O(N) to load an N-dimensional vector. Here, we show that it is possible to load an N-dimensional vector with a quantum circuit with polylogarithmic depth and entangled information in ancillary qubits. Results show that we can efficiently load data in quantum devices using a divide-and-conquer strategy to exchange computational time for space. We demonstrate a proof of concept on a real quantum device and present two applications for quantum machine learning. We expect that this new loading strategy allows the quantum speedup of tasks that require to load a significant volume of information to quantum devices.
