连续可变量子态的高效学习

Ya-Dong Wu, Yan Zhu, Giulio Chiribella, Nana Liu
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引用次数: 0

摘要

连续可变量子态的表征对于量子通信、传感、模拟和计算领域的应用至关重要。然而,要对多模量子态进行全面表征,需要进行大量实验,而实验数量会随着模数的增加呈指数增长。在这里,我们提出了一种替代方法,其目标不是重建完整的量子态,而是估算其在给定点上的特征函数。对于具有反射对称性的多模态,我们证明只需使用 O(logM) 份状态副本就能估算出 M 个点上的特征函数,而与模数无关。当已知特征函数为正时,如在挤压真空态的情况下,只需使用分光镜和同调测量,就能通过实验友好型装置实现估算。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Efficient learning of continuous-variable quantum states

Efficient learning of continuous-variable quantum states
The characterization of continuous-variable quantum states is crucial for applications in quantum communication, sensing, simulation, and computing. However, a full characterization of multimode quantum states requires a number of experiments that grows exponentially with the number of modes. Here we propose an alternative approach where the goal is not to reconstruct the full quantum state, but rather to estimate its characteristic function at a given set of points. For multimode states with reflection symmetry, we show that the characteristic function at M points can be estimated using only O(logM) copies of the state, independently of the number of modes. When the characteristic function is known to be positive, as in the case of squeezed vacuum states, the estimation is achieved by an experimentally friendly setup using only beamsplitters and homodyne measurements.
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CiteScore
8.60
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