论文标题
使用频域优化算法对量子系统的学习控制
Learning control of quantum systems using frequency-domain optimization algorithms
论文作者
论文摘要
我们通过在量子系统的超快激光器控制中使用频域优化算法来研究两类量子控制问题。在头等舱中，系统模型是已知的，并将基于频率梯度的优化算法应用于搜索最佳控制场，以选择性地和牢固地操纵原子rubidium中的种群传递。其他类别的量子控制问题涉及具有未知模型的实验系统。在这种情况下，我们引入了一种具有混合策略的差异进化算法，以搜索最佳控制场，并在超快激光控制实验中证明PR（HFAC）$ _ 3 $分子的能力。
We investigate two classes of quantum control problems by using frequency-domain optimization algorithms in the context of ultrafast laser control of quantum systems. In the first class, the system model is known and a frequency-domain gradient-based optimization algorithm is applied to searching for an optimal control field to selectively and robustly manipulate the population transfer in atomic Rubidium. The other class of quantum control problems involves an experimental system with an unknown model. In the case, we introduce a differential evolution algorithm with a mixed strategy to search for optimal control fields and demonstrate the capability in an ultrafast laser control experiment for the fragmentation of Pr(hfac)$_3$ molecules.
