控制复杂量子系统的粗粒度图像
Coarse-Grained Picture for Controlling Complex Quantum Systems
摘要：
我们提出了一个粗粒度的图片来控制"复杂“的量子动力学，即，多层次-多层次过渡与随机相互作用。假设最优控制动力学可以描述为初始状态和最终状态之间的拉比振荡，我们推导出一个解析最优域作为最优控制理论的解决方案。对于随机矩阵系统，我们用数值方法证实了解析最优场能使初始态转向目标态，这两个目标态都包含许多本征态。
英文摘要：
We propose a coarse-grained picture to control ``complex'' quantum dynamics, i.e., multi-level-multi-level transition with a random interaction. Assuming that optimally controlled dynamics can be described as a Rabi-like oscillation between an initial and final state, we derive an analytic optimal field as a solution to optimal control theory. For random matrix systems, we numerically confirm that the analytic optimal field steers an initial state to a target state which both contains many eigenstates.
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。
