Accessing the performance of CC2 for excited state dynamics: a benchmark study with pyrazine
Abstract
In this work, we access the performance of RI-CC2 for ultrafast internal conversion using pyrazine as a benchmark system. We implement analytical gradients and nonadiabatic coupling vectors for RI-CC2 in the Q-Chem package and employ them in two complementary approaches: a reduced-dimensionality vibronic coupling (VC) model and full-dimensional ab initio on-the-fly trajectory surface hopping simulations. To accelerate the on-the-fly dynamics, we employ a diabatic artificial neural network model trained on RI-CC2 data. Both the VC model and the full-dimensional dynamics reveal that the dark A1u state actively participates in the internal conversion process. RI-CC2 identifies the Q9a and Q8a vibrational modes as key drivers of the coherent population transfer between the A1u and B3u. The on-the-fly dynamics reproduce the experimental B2u population decay time of 26 fs, consistent with the measured value of 223 fs. The high-quality dataset of energies, forces, and nonadiabatic couplings generated here provides a valuable resource for future machine-learning developments, while the stochastic variant sRI-CC2 promises to extend such dynamics to larger molecular systems.
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