Photoinduced reactive dynamics of complex systems

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Photoinduced reactions are important processes in many chemical and biochemical systems. The detailed understanding of these processes often requires a rigorous quantum dynamical simulation of the nuclei involving numerous nonadiabatic transitions. The aim of this project is the development and application of numerical methods to facilitate a detailed quantum dynamical simulation of the nuclei in photoinduced processes of large systems. A central step for the quantum dynamical simulation of photoinduced reactive processes is the construction of high-dimensional ab initio potential energy surfaces (PESs) describing the couplings between electronic states. The present project focuses on the process driven construction of coupled PESs employing direct dynamics methods and neural network based fitting. The ab initio multiple spawning (AIMS) approach combined with a nonlinear dimensionality reduction method will be used to find and process relevant regions in the nonadiabatic dynamics of the system. Based on the ab initio data, vibronically coupled PESs will be constructed using modern neural network based fitting and other machine learning approaches. Multi-configurational time-dependent Hartree (MCTDH) calculations will be used to study the wavepacket dynamics on the resulting coupled PESs and to compute complex spectra which can not be accurately studied using trajectory based methods.Interesting applications include photoinduced dynamics of ethylene upon pi -> pi * excitation and the ring-opening reaction of pyridine.