Bogdain Florian, Mai Sebastian, González Leticia, Kühn Oliver
Institute of Physics, University of Rostock, Albert-Einstein-Str. 23-24, 18059 Rostock, Germany.
Institute of Theoretical Chemistry, Faculty of Chemistry, University of Vienna, Währinger Straße 17, 1090 Vienna, Austria.
Phys Chem Chem Phys. 2025 Jul 23;27(29):15609-15621. doi: 10.1039/d5cp01208b.
A protocol for generating potential energy surfaces and performing photoinduced nonadiabatic multidimensional wave packet propagation is presented. The workflow starts with the parameterization of a linear vibronic coupling (LVC) Hamiltonian using the Green's function - Bethe-Salpeter equation (BSE@GW) approach. In a second step, the LVC model is used as input for multi-layer multi-configurational time-dependent Hartree (ML-MCTDH) wave packet propagation. To facilitate automated ML tree generation, a spectral clustering algorithm is applied based on a correlation matrix obtained from nuclear coordinate expectation values of a full-dimensional time-dependent Hartree (TDH) simulation. The performance of the protocol is tested on the photoinduced spin-vibronic dynamics of a transition metal complex, [Fe(cpmp)]. For this example, it is shown that BSE@GW provides a more robust description of the character of the transitions contributing to the absorption spectrum compared to TD-DFT. Furthermore, the LVC parameterization is tested against explicit calculations of potential energy curves to find the validity of the linear approximation over a wide range of normal mode elongation. Finally, the flexibility of spectral clustering is used to generate different ML trees, resulting in very different numerical efficiencies for ML-MCTDH propagation. In terms of electronic structure and dimensionality, [Fe(cpmp)] is a challenging example, suggesting that the new protocol should be applicable to a wide range of systems.
本文提出了一种用于生成势能面并进行光诱导非绝热多维波包传播的协议。工作流程首先使用格林函数 - 贝塞耳 - 萨尔皮特方程（BSE@GW）方法对线性振子耦合（LVC）哈密顿量进行参数化。第二步，将LVC模型用作多层多组态含时哈特里（ML-MCTDH）波包传播的输入。为了便于自动生成ML树，基于从全维含时哈特里（TDH）模拟的核坐标期望值获得的相关矩阵应用了一种谱聚类算法。该协议的性能在过渡金属配合物[Fe(cpmp)]的光诱导自旋 - 振子动力学上进行了测试。对于这个例子，结果表明与TD-DFT相比，BSE@GW对有助于吸收光谱的跃迁特征提供了更稳健的描述。此外，针对势能曲线的显式计算对LVC参数化进行了测试，以确定在广泛的正则模伸长范围内线性近似的有效性。最后，利用谱聚类的灵活性生成不同的ML树，导致ML-MCTDH传播的数值效率有很大差异。就电子结构和维度而言，[Fe(cpmp)]是一个具有挑战性的例子，这表明新协议应适用于广泛的系统。
