High-dimensional quantum encoding via photon-subtracted squeezed states
High-dimensional quantum encoding via photon-subtracted squeezed states
复制标题
DOI：
10.1103/physreva.99.022342
复制
发表时间：
2018-11
影响因子：
2.9
通讯作者：
F. Arzani;A. Ferraro;V. Parigi
中科院分区：
文献类型：
--
作者：
F. Arzani;A. Ferraro;V. Parigi
我们介绍了一种基于多模压缩态相干模相关单光子相减的高维量子编码。这种编码可以看作是对标准单光子多轨编码的非零压缩情况的推广。其优点是，压缩的存在使得在连续变量量子处理中能够使用常见的工具，这反过来又允许表明，通过简单地调整选通光子减法方案的经典场，可以生成和检测任意d能级量子态。因此，该方案适用于映射任意量子力学形式的经典数据。无论数据集字母表的维度如何，映射的条件是仅减去单个光子，使其几乎是无条件的。我们证明了这种编码可以用于计算向量距离，这是各种量子机器学习算法中的关键原语。
We introduce a high-dimensional quantum encoding based on coherent mode-dependent single-photon subtraction from multimode squeezed states. This encoding can be seen as a generalization to the case of non-zero squeezing of the standard single-photon multi-rail encoding. The advantage is that the presence of squeezing enables the use of common tools in continuous-variable quantum processing, which in turn allows to show that arbitrary d-level quantum states can be generated and detected via simply tuning the classical fields that gates the photon-subtraction scheme. Therefore, the scheme is suitable for mapping arbitrary classical data in quantum mechanical form. Regardless the dimension of the data set alphabet, the mapping is conditioned on the subtraction of a single photon only, making it nearly unconditional. We prove that this encoding can be used to calculate vector distances, a pivotal primitive in various quantum machine learning algorithms.