非正交振幅放大用于混合连续变量-离散变量量子处理器

中文摘要 AI 辅助

我们提出了一种用于混合连续变量-离散变量（CV-DV）量子处理器的非正交振幅放大（NOAA）方法，其中可用的CV辅助投影仪对目标态并非完美选择。我们建立了可实现的目标态保真度的界限，该界限由初始目标态振幅和可访问反射算子的选择性决定。此界限限制了NOAA在混合CV-DV系统中的性能。为缓解此限制，我们提出使用压缩CV辅助量子比特来减少相关CV态之间的重叠，并使用混合量子信号处理（HQSP）滤波器来抑制因目标本征能量知识不完善而产生的误差。数值模拟表明，对于较小的初始目标态振幅，尽管存在非正交性，我们的协议在保真度和效率上均优于重复直至成功（RUS）方法。对于较大的初始振幅，RUS已足够高效，振幅放大提供的额外优势甚微。

英文摘要

We introduce a non-orthogonal amplitude amplification (NOAA) method for hybrid continuous-variable- discrete-variable (CV-DV) quantum processors, where the available CV-assisted projector is not perfectly se- lective for the target state. We establish a bound on the achievable target-state fidelity, which is determined by the initial target-state amplitude and the selectivity of the accessible reflection operator. This bound limits the performance of NOAA in hybrid CV-DV systems. To mitigate this limitation, we propose using a squeezed CV ancilla to reduce the overlap between relevant CV states and a hybrid quantum signal processing (HQSP) filter to suppress errors arising from imperfect knowledge of the target eigenenergy. Numerical simulations show that, for small initial target-state amplitudes, our protocol achieves higher fidelity and efficiency than the repeat-until-success (RUS) method despite the presence of non-orthogonality. For large initial amplitudes, RUS is already efficient, and amplitude amplification provides little additional advantage.

发表机构

• North Carolina State University（北卡罗来纳州立大学）

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