论文标题
自适应测量过滤器：最佳量子马尔可夫链的有效策略
Adaptive measurement filter: efficient strategy for optimal estimation of quantum Markov chains
论文作者
论文摘要
连续时间测量对于量子工程和量子控制的多种任务具有重要作用，包括估计通过环境监测的开放量子系统的动态参数。但是，此类测量并不是提取输出状态下可用的最大信息，因此寻找替代性最佳测量策略是一个主要的开放问题。 在本文中，我们在离散时间输入输出量子马尔可夫链的设置中解决了这个问题。我们提出了一种有效的算法，以最佳估计一维动力学参数，该参数包括一个迭代过程，用于更新“测量过滤器”操作员并确定输出单元的连续测量库。该方案的关键要素是使用相干量子吸收器作为与系统相互作用后输出的后处理方式。这是自适应设计的，以使关节系统和吸收器固定态在参考参数值下是纯净的。该计划为最佳的连续时间自适应测量提供了令人兴奋的前景，但是需要更多的工作才能找到现实的实际实现。
Continuous-time measurements are instrumental for a multitude of tasks in quantum engineering and quantum control, including the estimation of dynamical parameters of open quantum systems monitored through the environment. However, such measurements do not extract the maximum amount of information available in the output state, so finding alternative optimal measurement strategies is a major open problem. In this paper we solve this problem in the setting of discrete-time input-output quantum Markov chains. We present an efficient algorithm for optimal estimation of one-dimensional dynamical parameters which consists of an iterative procedure for updating a `measurement filter' operator and determining successive measurement bases for the output units. A key ingredient of the scheme is the use of a coherent quantum absorber as a way to post-process the output after the interaction with the system. This is designed adaptively such that the joint system and absorber stationary state is pure at a reference parameter value. The scheme offers an exciting prospect for optimal continuous-time adaptive measurements, but more work is needed to find realistic practical implementations.
