Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2604.05734 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866918431146639360 |
|---|---|
| author | Bi, Rui-Hao Zhao, Chongxiao Sun, Ruixin Dou, Wenjie |
| author_facet | Bi, Rui-Hao Zhao, Chongxiao Sun, Ruixin Dou, Wenjie |
| contents | 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 $A_\text{1u}$ state actively participates in the internal conversion process. RI-CC2 identifies the $Q_\text{9a}$ and $Q_\text{8a}$ vibrational modes as key drivers of the coherent population transfer between the $A_\text{1u}$ and $B_\text{3u}$. The on-the-fly dynamics reproduce the experimental $B_\text{2u}$ population decay time of 26 fs, consistent with the measured value of $22\pm3$ 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_05734 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Accessing the performance of CC2 for excited state dynamics: a benchmark study with pyrazine Bi, Rui-Hao Zhao, Chongxiao Sun, Ruixin Dou, Wenjie Chemical Physics 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 $A_\text{1u}$ state actively participates in the internal conversion process. RI-CC2 identifies the $Q_\text{9a}$ and $Q_\text{8a}$ vibrational modes as key drivers of the coherent population transfer between the $A_\text{1u}$ and $B_\text{3u}$. The on-the-fly dynamics reproduce the experimental $B_\text{2u}$ population decay time of 26 fs, consistent with the measured value of $22\pm3$ 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. |
| title | Accessing the performance of CC2 for excited state dynamics: a benchmark study with pyrazine |
| topic | Chemical Physics |
| url | https://arxiv.org/abs/2604.05734 |