Nondirect-Product Local Diabatic Representation with Smolyak Sparse Grids
Modeling nonadiabatic conical intersection dynamics is critical for understanding a wide range of photophysical, photochemical, and biological phenomena. Here we develop a nonadiabatic conical intersection wave packet dynamic method in the local diabatic representation using Smolyak sparse grids. Employing sparse grids avoids the direct-product grids in configuration space and alleviates the exponential scaling of computation costs with the molecular size. Numerical demonstrations are first performed for a two-dimensional vibronic model of pyrazine, where the results using sparse grids are in excellent agreement with those using direct-product grids, with sparse grids being much faster. Moreover, we demonstrate that for a four-dimensional pyrazine model, where direct-product grids are computationally infeasible, sparse grids can provide almost exact results. The sparse grid local diabatic representation method is further applied to a realistic model system of phenol photodissociation with much more complex potential energy surfaces; the results using sparse grids still agree very well with the direct-product grids. Finally, by combining with electronic structure calculations, we apply our method to the Shin-Metiu model without quasi-diabatization. The sparse grid and direct-product grid results are in good agreement, with the sparse grid computational cost being half of the full grid.
Authors
- Ahai Chen (ORCID: https://orcid.org/0000-0002-8584-7870)
- Xiaotong Zhu (ORCID: https://orcid.org/0009-0003-9892-7591)
- Bing Gu (ORCID: https://orcid.org/0000-0002-5787-3334)
- Yukun Yang (ORCID: https://orcid.org/0000-0002-7854-5452)
- Yujuan Xie (ORCID: https://orcid.org/0000-0003-2116-7160)
Institutions
- ShanghaiTech University (CN)
- Westlake University (CN)
- Henan Normal University (CN)
Publication Details
- Journal
- Journal of Chemical Theory and Computation
- Published
- 2024-10-16
- DOI
- https://doi.org/10.1021/acs.jctc.4c00673
- Citations
- 4
- Primary Topic
- Markov Chains and Monte Carlo Methods
- Type
- article
- Field-Weighted Citation Impact
- 2.84
Funders
- National Natural Science Foundation of China