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首页> 外文期刊>The journal of physical chemistry, A. Molecules, spectroscopy, kinetics, environment, & general theory >Quantum Trajectory Mean-Field Method for Nonadiabatic Dynamics in Photochemistry
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Quantum Trajectory Mean-Field Method for Nonadiabatic Dynamics in Photochemistry

机译：光化学中非抗脂肪动力学的量子轨迹均值法

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摘要

The mixed quantum-classical dynamical approaches have been widely used to study nonadiabatic phenomena in photochemistry and photobiology, in which the time evolutions of the electronic and nuclear subsystems are treated based on quantum and classical mechanics, respectively. The key issue is how to deal with coherence and decoherence during the propagation of the two subsystems, which has been the subject of numerous investigations for a few decades. A brief description on Ehrenfest mean-field and surface-hopping (SH) methods is first provided, and then different algorithms for treatment of quantum decoherence are reviewed in the present paper. More attentions were paid to quantum trajectory meanfield (QTMF) method under the picture of quantum measurements, which is able to overcome the overcoherence problem. Furthermore, the combined QTMF and SH algorithm is proposed in the present work, which takes advantages of the QTMF and SH methods. The potential to extend the applicability of the QTMF method was briefly discussed, such as the generalization to other type of nonadiabatic transitions, the combination with multiscale computational models, and possible improvements on its accuracy and efficiency by using machine-learning techniques.
机译：混合量子古典动力学方法已被广泛用于研究光化学和光生物学中的非等离现象，其中电子和核子系统的时间演变分别基于量子和经典力学处理。关键问题是如何处理两年子系统的传播过程中的一致性和变阻，这是几十年来的众多调查的主题。首先提供关于Ehfest平均场和表面跳跃（SH）方法的简要说明，然后在本文中审查了用于治疗量子脱机的不同算法。在量子测量图片下，可以获得更多的注意力为量子轨迹平均域（QTMF）方法，这能够克服综合体问题。此外，在本作工作中提出了组合的QTMF和SH算法，其采用QTMF和SH方法的优点。简要讨论了延长QTMF方法的适用性的可能性，例如通过使用机器学习技术的多尺度计算模型的概括，与多尺寸计算模型的组合，以及可能改善其通过机器学习技术的准确性和效率的组合。

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