Iterative maximum-likelihood reconstruction in quantum homodyne tomography
Iterative maximum-likelihood reconstruction in quantum homodyne tomography
复制标题
DOI：
10.1088/1464-4266/6/6/014
复制
发表时间：
2004-06-01
期刊：
影响因子：
--
通讯作者：
Lvovsky, AI
中科院分区：
文献类型：
--
作者：
Lvovsky, AI
我提出了一个迭代的期望最大化算法，用于从一组平衡的零差测量重构光学系综的密度矩阵。该算法直接应用于采集的数据，绕过计算边缘分布的中间步骤。通过与传统的逆Radon变换技术的比较，表明了新方法的优越性。
I propose an iterative expectation maximization algorithm for reconstructing the density matrix of an optical ensemble from a set of balanced homodyne measurements. The algorithm applies directly to the acquired data, bypassing the intermediate step of calculating marginal distributions. The advantages of the new method are made manifest by comparing it with the traditional inverse Radon transformation technique.