NATPS: Nonadiabatic Transition Path Sampling Using Time-Reversible MASH Dynamics
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| Main Authors: | , , , , , |
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| Format: | Preprint |
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2026
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| _version_ | 1866913131621515264 |
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| author | Yang, Xiran Reiner, Madlen Maria Bachmair, Brigitta González, Leticia Dietschreit, Johannes C. B. Dellago, Christoph |
| author_facet | Yang, Xiran Reiner, Madlen Maria Bachmair, Brigitta González, Leticia Dietschreit, Johannes C. B. Dellago, Christoph |
| contents | Rare nonadiabatic events play a central role in photochemistry but remain difficult to simulate because excited-state dynamics is computationally demanding and often stochastic. Here we introduce a deterministic and time-reversible implementation of nonadiabatic dynamics that enables the application of transition path sampling (TPS) to excited-state processes. Our approach builds on the Mapping Approach to Surface Hopping (MASH) and establishes the conditions required for path ensemble sampling, in particular time reversibility and detailed balance. Combining this dynamics with the TPS framework yields a new method, termed nonadiabatic transition path sampling (NATPS).
Using a model system of electronically coupled potential energy surfaces, we demonstrate that NATPS efficiently generates ensembles of reactive trajectories and provides mechanistic insight into nonadiabatic pathways. Compared with brute-force trajectory simulations and forward-flux sampling approaches, NATPS substantially reduces the computational effort required to obtain reactive trajectories. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_08677 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | NATPS: Nonadiabatic Transition Path Sampling Using Time-Reversible MASH Dynamics Yang, Xiran Reiner, Madlen Maria Bachmair, Brigitta González, Leticia Dietschreit, Johannes C. B. Dellago, Christoph Computational Physics Chemical Physics Rare nonadiabatic events play a central role in photochemistry but remain difficult to simulate because excited-state dynamics is computationally demanding and often stochastic. Here we introduce a deterministic and time-reversible implementation of nonadiabatic dynamics that enables the application of transition path sampling (TPS) to excited-state processes. Our approach builds on the Mapping Approach to Surface Hopping (MASH) and establishes the conditions required for path ensemble sampling, in particular time reversibility and detailed balance. Combining this dynamics with the TPS framework yields a new method, termed nonadiabatic transition path sampling (NATPS). Using a model system of electronically coupled potential energy surfaces, we demonstrate that NATPS efficiently generates ensembles of reactive trajectories and provides mechanistic insight into nonadiabatic pathways. Compared with brute-force trajectory simulations and forward-flux sampling approaches, NATPS substantially reduces the computational effort required to obtain reactive trajectories. |
| title | NATPS: Nonadiabatic Transition Path Sampling Using Time-Reversible MASH Dynamics |
| topic | Computational Physics Chemical Physics |
| url | https://arxiv.org/abs/2603.08677 |