Ab Initio Molecular Cavity Quantum Electrodynamics Simulations Using Machine Learning Models.
Ab Initio Molecular Cavity Quantum Electrodynamics Simulations Using Machine Learning Models.
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使用机器学习模型的从头算分子腔量子电动力学模拟。
DOI：
10.1021/acs.jctc.3c00137
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发表时间：
2023-04-25
影响因子：
5.5
通讯作者：
Huo, Pengfei
中科院分区：
文献类型：
--
作者：
Hu, Deping;Huo, Pengfei
我们提出了分子-腔混合系统极化子动力学的混合量子经典模拟。特别是，我们将耦合电子-光子自由度（DOF）视为量子子系统，将核自由度视为经典子系统，并使用轨迹表面跳跃方法来模拟由于核耦合运动而导致的极化子态之间的非绝热动力学。我们使用从泡利-菲尔兹量子电动力学哈密顿量导出的精确核梯度表达式，而不进行进一步的近似。分子系统的能量、梯度和导数耦合是通过完全活性空间自洽场（CASSCF）水平的动态模拟获得的，用于计算极化子能量和核梯度。偶极子的导数也是极化子核梯度表达中的必要成分，但在电子结构方法中通常不容易获得。为了应对这一挑战，我们使用机器学习模型和核岭回归方法来构造偶极子并进一步获得其导数，与 CASSCF 理论处于同一水平。空腔损耗过程是用 Lindblad 跳跃超级算子对电子-光子量子子系统的密度降低进行建模的。我们研究了偶氮甲烷分子及其在腔内的光致异构化动力学。我们的结果显示了机器学习偶极子的准确性及其在模拟极化子动力学中的用途。我们的极化子动力学结果还表明，通过耦合到光学腔并改变光-物质耦合强度和腔损失率，可以有效地调节偶氮甲烷的异构化反应。
We present a mixed quantum-classical simulation of polariton dynamics for molecule–cavity hybrid systems. In particular, we treat the coupled electronic–photonic degrees of freedom (DOFs) as the quantum subsystem and the nuclear DOFs as the classical subsystem and use the trajectory surface hopping approach to simulate non-adiabatic dynamics among the polariton states due to the coupled motion of nuclei. We use the accurate nuclear gradient expression derived from the Pauli–Fierz quantum electrodynamics Hamiltonian without making further approximations. The energies, gradients, and derivative couplings of the molecular systems are obtained from the on-the-fly simulations at the level of complete active space self-consistent field (CASSCF), which are used to compute the polariton energies and nuclear gradients. The derivatives of dipoles are also necessary ingredients in the polariton nuclear gradient expression but are often not readily available in electronic structure methods. To address this challenge, we use a machine learning model with the Kernel ridge regression method to construct the dipoles and further obtain their derivatives, at the same level as the CASSCF theory. The cavity loss process is modeled with the Lindblad jump superoperator on the reduced density of the electronic–photonic quantum subsystem. We investigate the azomethane molecule and its photoinduced isomerization dynamics inside the cavity. Our results show the accuracy of the machine-learned dipoles and their usage in simulating polariton dynamics. Our polariton dynamics results also demonstrate the isomerization reaction of azomethane can be effectively tuned by coupling to an optical cavity and by changing the light–matter coupling strength and the cavity loss rate.
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影响因子：
64.8
作者：
Chikkaraddy R;de Nijs B;Benz F;Barrow SJ;Scherman OA;Rosta E;Demetriadou A;Fox P;Hess O;Baumberg JJ
通讯作者：
Baumberg JJ
影响因子：
5.5
作者：
Flick J;Appel H;Ruggenthaler M;Rubio A
通讯作者：
Rubio A
用于多原子系统非绝热分子动力学的动态表面跳跃程序 JADE：实现和应用
影响因子：
5.5
作者：
Du, Likai;Lan, Zhenggang
通讯作者：
Lan, Zhenggang
影响因子：
7
作者：
Feist, Johannes;Galego, Javier;Garcia-Vidal, Francisco J.
通讯作者：
Garcia-Vidal, Francisco J.
影响因子：
8.6
作者：
GROSS, EKU;KOHN, W
通讯作者：
KOHN, W