Department of Chemistry and Chemical Biology, Cornell University, New York, Ithaca 14853, USA.
Currently at Laboratory of Theoretical Physical Chemistry, Institut des Sciences et Ingénierie Chimiques, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne CH-1015, Switzerland.
J Chem Phys. 2017 Jun 21;146(23):234104. doi: 10.1063/1.4986645.
The Mixed Quantum-Classical Initial Value Representation (MQC-IVR) is a recently introduced approximate semiclassical (SC) method for the calculation of real-time quantum correlation functions. MQC-IVR employs a modified Filinov filtration (MFF) scheme to control the overall phase of the SC integrand, extending the applicability of SC methods to complex systems while retaining their ability to accurately describe quantum coherence effects. Here, we address questions regarding the effectiveness of the MFF scheme in combination with SC dynamics. Previous work showed that this filtering scheme is of limited utility in the context of semiclassical wavepacket propagation, but we find that the MFF is extraordinarily powerful in the context of correlation functions. By examining trajectory phase and amplitude contributions to the real-time SC correlation function in a model system, we clearly demonstrate that the MFF serves to reduce noise by damping amplitude only in regions of highly oscillatory phase leading to a reduction in computational effort while retaining accuracy. Further, we introduce a novel and efficient MQC-IVR formulation that allows for linear scaling in computational cost with the total simulation length, a significant improvement over the more-than quadratic scaling exhibited by the original method.
混合量子经典初始值表示（MQC-IVR）是一种最近引入的近似半经典（SC）方法，用于计算实时量子相关函数。MQC-IVR 采用改进的 Filinov 滤波（MFF）方案来控制 SC 积分的整体相位，从而扩展了 SC 方法在复杂系统中的适用性，同时保留了其准确描述量子相干效应的能力。在这里，我们将讨论与 SC 动力学相结合的 MFF 方案的有效性问题。以前的工作表明，在半经典波包传播的背景下，这种滤波方案的效用有限，但我们发现 MFF 在相关函数的背景下非常强大。通过在模型系统中检查轨迹相位和振幅对实时 SC 相关函数的贡献，我们清楚地证明，MFF 通过仅在导致计算工作量减少的高度振荡相位区域中阻尼振幅来降低噪声，同时保持准确性。此外，我们引入了一种新颖而有效的 MQC-IVR 公式，允许在计算成本上与总模拟长度呈线性比例，与原始方法表现出的超过二次比例相比有显著改进。
