Real-time frequency estimation of a qubit without single-shot-readout
Real-time frequency estimation of a qubit without single-shot-readout
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DOI：
10.1088/2058-9565/acd415
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发表时间：
2022-10
影响因子：
6.7
通讯作者：
Inbar Zohar;B. Haylock;Y. Romach;M. Arshad;Nir Halay;Niv Drucker;R. Stöhr;A. Denisenko;Yonatan Cohen;C. Bonato;A. Finkler
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作者：
Inbar Zohar;B. Haylock;Y. Romach;M. Arshad;Nir Halay;Niv Drucker;R. Stöhr;A. Denisenko;Yonatan Cohen;C. Bonato;A. Finkler
量子传感器可以使用量子算法在大的动态范围内潜在地实现灵敏度的海森堡极限。自适应相位估计算法（PEA）是一个例子，它被证明可以实现这种高灵敏度与单次读取（SSR）传感器。然而，由于测量的低对比度性质，在非SSR传感器上使用自适应PEA并非微不足道。在该PEA算法中，考虑测量的平均性质的标准方法是使用基于“多数表决”的方法。虽然它很容易实现，但由于测量中的噪声，这种方法更容易出错。为了减少这些错误，最近从理论上证明了批次选择的二项分布技术具有上级优势，因为考虑了平均测量的所有结果范围。在这里，我们申请，第一次，实时非自适应PEA的非SSR传感器与二项分布的方法。我们比较的均方误差的二项分布的方法，多数表决的方法，在环境条件下使用的金刚石中的氮空位中心作为非SSR传感器。我们的研究结果表明，二项分布的方法实现了更好的准确性与相同的感测时间。为了进一步缩短感测时间，我们提出了一种自适应算法，控制读出相位，因此，测量基集。我们通过数值模拟表明，加入自适应协议可以进一步提高精度，在未来的实时实验。
Quantum sensors can potentially achieve the Heisenberg limit of sensitivity over a large dynamic range using quantum algorithms. The adaptive phase estimation algorithm (PEA) is one example that was proven to achieve such high sensitivities with single-shot readout (SSR) sensors. However, using the adaptive PEA on a non-SSR sensor is not trivial due to the low contrast nature of the measurement. The standard approach to account for the averaged nature of the measurement in this PEA algorithm is to use a method based on ‘majority voting’. Although it is easy to implement, this method is more prone to mistakes due to noise in the measurement. To reduce these mistakes, a binomial distribution technique from a batch selection was recently shown theoretically to be superior, as all ranges of outcomes from an averaged measurement are considered. Here we apply, for the first time, real-time non-adaptive PEA on a non-SSR sensor with the binomial distribution approach. We compare the mean square error of the binomial distribution method to the majority-voting approach using the nitrogen-vacancy center in diamond at ambient conditions as a non-SSR sensor. Our results suggest that the binomial distribution approach achieves better accuracy with the same sensing times. To further shorten the sensing time, we propose an adaptive algorithm that controls the readout phase and, therefore, the measurement basis set. We show by numerical simulation that adding the adaptive protocol can further improve the accuracy in a future real-time experiment.