Jiráková Kateřina, Černoch Antonín, Barasiński Artur, Lemr Karel
Institute of Physics of the Academy of Sciences of the Czech Republic, Joint Laboratory of Optics of Palacký University and Institute of Physics AS CR, 17. listopadu 50a, 772 07, Olomouc, Czech Republic.
Institute of Theoretical Physics, University of Wroclaw, Plac Maxa Borna 9, 50-204, Wroclaw, Poland.
Sci Rep. 2024 Jul 16;14(1):16374. doi: 10.1038/s41598-024-65385-7.
This research analyzes the adverse impact of white noise on collective quantum measurements and argues that such noise poses a significant obstacle for the otherwise straightforward deployment of collective measurements in quantum communications. Our findings then suggests addressing this issue by correlating outcomes of these measurements with quantum state purity. To test the concept, a support vector machine is employed to boost the performance of several collective entanglement witnesses by incorporating state purity into the classification task of distinguishing entangled states from separable ones. Furthermore, the application of machine learning allows to optimize specificity of entanglement detection given a target value of sensitivity. A response operating characteristic curve is reconstructed based on this optimization and the area under curve calculated to assess the efficacy of the proposed model. Finally, we test the presented approach on an experimental dataset of Werner states.
本研究分析了白噪声对集体量子测量的不利影响，并认为这种噪声对量子通信中集体测量原本直接的部署构成了重大障碍。我们的研究结果表明，通过将这些测量的结果与量子态纯度相关联来解决这个问题。为了测试这个概念，采用支持向量机，通过将态纯度纳入区分纠缠态和可分态的分类任务中，来提高几个集体纠缠见证者的性能。此外，机器学习的应用允许在给定灵敏度目标值的情况下优化纠缠检测的特异性。基于这种优化重建响应操作特性曲线，并计算曲线下面积以评估所提出模型的有效性。最后，我们在维纳态的实验数据集上测试了所提出的方法。
