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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.
|Number of pages||11|
|Journal||Physical Review A (Atomic, Molecular, and Optical Physics)|
|Publication status||Published - 28 Feb 2019|
Arzani, F., Ferraro, A., & Parigi, V. (2019). High-dimensional quantum encoding via photon-subtracted squeezed states. Physical Review A (Atomic, Molecular, and Optical Physics), 99(2), . https://doi.org/10.1103/PhysRevA.99.022342