论文标题
自适应量子层析成像和迭代粒子过滤
Adaptive quantum state tomography with iterative particle filtering
论文作者
论文摘要
已经开发了几种基于贝叶斯估计的启发式方法来执行量子状态断层扫描（QST）。他们使用区域估计器量化不确定性并包括实验者的先验知识的能力使该方法家族成为QST的吸引人选择。但是，纯状态的专门技术对于混合国家来说不能很好地工作，反之亦然。在本文中，我们提出了一种基于自适应粒子滤波器（PF）的QST协议，该方案与非适应性贝叶斯方案相比，改善了保真度的缩放度。这是由于该协议的毅力是找到各州的对角线基础的，以及在流行的PF方法中更系统地处理与信息性先验的主观性有关的持久问题以及重新采样器产生的颗粒的无效性。 IBM量子设备上的数值示例和实施表明，任意量子状态的性能和我们提出的方案的应用程序准备性的提高。
Several Bayesian estimation based heuristics have been developed to perform quantum state tomography (QST). Their ability to quantify uncertainties using region estimators and include a priori knowledge of the experimentalists makes this family of methods an attractive choice for QST. However, specialized techniques for pure states do not work well for mixed states and vice versa. In this paper, we present an adaptive particle filter (PF) based QST protocol which improves the scaling of fidelity compared to nonadaptive Bayesian schemes for arbitrary multi-qubit states. This is due to the protocol's unabating perseverance to find the states's diagonal bases and more systematic handling of enduring problems in popular PF methods relating to the subjectivity of informative priors and the invalidity of particles produced by resamplers. Numerical examples and implementation on IBM quantum devices demonstrate improved performance for arbitrary quantum states and the application readiness of our proposed scheme.
