Shuang Feng, Rabitz Herschel
Department of Chemistry, Princeton University, Princeton, New Jersey 08544, USA.
J Chem Phys. 2004 Nov 15;121(19):9270-8. doi: 10.1063/1.1799591.
This paper investigates the impact of control field noise on the optimal manipulation of quantum dynamics. Simulations are performed on several multilevel quantum systems with the goal of population transfer in the presence of significant control noise. The noise enters as run-to-run variations in the control amplitude and phase with the observation being an ensemble average over many runs as is commonly done in the laboratory. A genetic algorithm with an improved elitism operator is used to find the optimal field that either fights against or cooperates with control field noise. When seeking a high control yield it is possible to find fields that successfully fight with the noise while attaining good quality stable results. When seeking modest control yields, fields can be found which are optimally shaped to cooperate with the noise and thereby drive the dynamics more efficiently. In general, noise reduces the coherence of the dynamics, but the results indicate that population transfer objectives can be met by appropriately either fighting or cooperating with noise, even when it is intense.
本文研究了控制场噪声对量子动力学最优操控的影响。针对几个多能级量子系统进行了模拟，目的是在存在显著控制噪声的情况下实现布居转移。噪声以控制幅度和相位的逐次运行变化形式进入，观测结果是如实验室中通常所做的那样对多次运行的系综平均。使用具有改进精英算子的遗传算法来寻找与控制场噪声对抗或合作的最优场。当寻求高控制产率时，有可能找到能成功对抗噪声并同时获得高质量稳定结果的场。当寻求适度控制产率时，可以找到形状最优以与噪声合作从而更有效地驱动动力学的场。一般来说，噪声会降低动力学的相干性，但结果表明，即使噪声很强，通过适当地与噪声对抗或合作仍可实现布居转移目标。
