密度矩阵的极大似然估计
Maximum-likelihood estimation of the density matrix
摘要：
本文提出了一种基于极大似然方法的量子态估计的通用方法。这种方法提供了一个正定估计的密度矩阵从一系列的测量上执行相同的准备副本的系统。该方法是通用的，可以应用到多模辐射场以及自旋系统。在极大似然策略中，自然会引入物理约束，从而大大减少统计误差。数值实现的方法是基于一个特定形式的高斯分解正定厄米矩阵。
英文摘要：
We present a universal technique for quantum state estimation based on the maximum-likelihood method. This approach provides a positive definite estimate for the density matrix from a sequence of measurements performed on identically prepared copies of the system. The method is versatile and can be applied to multimode radiation fields as well as to spin systems. The incorporation of physical constraints, which is natural in the maximum-likelihood strategy, leads to a substantial reduction of statistical errors. Numerical implementation of the method is based on a particular form of the Gauss decomposition for positive definite Hermitian matrices.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
