论文标题
使用变异量子电路估算非马克维亚度的程度
Estimating the degree of non-Markovianity using variational quantum circuits
论文作者
论文摘要
量子机学习(QML)的几种应用依赖于使用测量结果训练算法的量子测量。但是,最近开发的QML模型(例如变分量子电路(VQC))可以直接在量子系统状态(量子数据)上实现。在这里,我们建议使用量子量作为探测,以估计环境的非马克维亚程度。使用VQC,我们发现了Qubit-Anvormentment相互作用的最佳序列,该序列可对振幅阻尼,相阻尼和两种模型的组合的非马克维亚性程度进行准确的估计。我们介绍了基于问题的ANSATZ,该ANSATZ在探针量子量和与环境的交互时间上进行了优化。这项工作有助于VQC的实用量子应用,并提供了可行的实验程序来估计非马克维亚性程度。
Several applications of quantum machine learning (QML) rely on a quantum measurement followed by training algorithms using the measurement outcomes. However, recently developed QML models, such as variational quantum circuits (VQCs), can be implemented directly on the state of the quantum system (quantum data). Here, we propose to use a qubit as a probe to estimate the degree of non-Markovianity of the environment. Using VQCs, we find an optimal sequence of qubit-environment interactions that yield accurate estimations of the degree of non-Markovianity for the amplitude damping, phase damping, and the combination of both models. We introduce a problem-based ansatz that optimizes upon the probe qubit and the interaction time with the environment. This work contributes to practical quantum applications of VQCs and delivers a feasible experimental procedure to estimate the degree of non-Markovianity.