论文标题
将控制景观和层析成像原理汇总在一起
Drawing together control landscape and tomography principles
论文作者
论文摘要
使用形状字段控制量子系统的能力以及从测量数据中推断此类受控系统的状态是量子设备的设计和操作中的关键任务。在这里，我们将执行这两个任务的成功与基础控制景观的结构联系起来。我们将控制和重建系统的完整状态的能力与缺乏奇异控制的能力联系起来，并表明在足够长的演化时间中，很少发生奇异控制。基于这些发现，我们描述了一种学习算法，用于查找最佳控件，该算法利用从部分访问系统获得的测量数据。讨论了由于高维系统中测量现象的集中度引起的开放挑战。
The ability to control quantum systems using shaped fields as well as to infer the states of such controlled systems from measurement data are key tasks in the design and operation of quantum devices. Here we associate the success of performing both tasks to the structure of the underlying control landscape. We relate the ability to control and reconstruct the full state of the system to the absence of singular controls, and show that for sufficiently long evolution times singular controls rarely occur. Based on these findings, we describe a learning algorithm for finding optimal controls that makes use of measurement data obtained from partially accessing the system. Open challenges stemming from the concentration of measure phenomenon in high dimensional systems are discussed.
