ARC Centre for Engineered Quantum Systems, School of Physics, The University of Sydney, Sydney, NSW, 2006, Australia.
National Measurement Institute, West Lindfield, NSW, 2070, Australia.
Nat Commun. 2017 Dec 19;8(1):2189. doi: 10.1038/s41467-017-02298-2.
Essential to the functionality of qubit-based sensors are control protocols, which shape their response in frequency space. However, in common control routines out-of-band spectral leakage complicates interpretation of the sensor's signal. In this work, we leverage discrete prolate spheroidal sequences (a.k.a. Slepian sequences) to synthesize provably optimal narrowband controls ideally suited to spectral estimation of a qubit's noisy environment. Experiments with trapped ions demonstrate how spectral leakage may be reduced by orders of magnitude over conventional controls when a near resonant driving field is modulated by Slepians, and how the desired narrowband sensitivity may be tuned using concepts from RF engineering. We demonstrate that classical multitaper techniques for spectral analysis can be ported to the quantum domain and combined with Bayesian estimation tools to experimentally reconstruct complex noise spectra. We then deploy these techniques to identify previously immeasurable frequency-resolved amplitude noise in our qubit's microwave synthesis chain.
基于量子位的传感器的功能的关键是控制协议，它在频率空间中塑造传感器的响应。然而，在常见的控制例程中，带外频谱泄漏使传感器信号的解释变得复杂。在这项工作中，我们利用离散拉长球序列（也称为斯雷皮恩序列）来合成可证明的最优窄带控制，非常适合于量子位嘈杂环境的频谱估计。囚禁离子的实验表明，当接近共振的驱动场通过斯雷皮恩调制时，与传统控制相比，频谱泄漏可以减少几个数量级，以及如何使用射频工程的概念来调整所需的窄带灵敏度。我们证明了用于频谱分析的经典多峰技术可以移植到量子领域，并与贝叶斯估计工具结合使用，以实验重建复杂的噪声谱。然后，我们将这些技术用于识别我们的量子位微波合成链中以前无法测量的频率分辨幅度噪声。
