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NATPS: Nonadiabatic Transition Path Sampling Using the Time-Reversible Mapping Approach to Surface Hopping.

Xiran Yang1,2,3, Madlen Maria Reiner2,4,5, Brigitta Bachmair1,2,3

  • 1Institute of Theoretical Chemistry, Faculty of Chemistry, University of Vienna, Währinger Straße 17, 1090 Vienna, Austria.

The Journal of Physical Chemistry Letters
|May 13, 2026
PubMed
Summary
This summary is machine-generated.

We developed nonadiabatic transition path sampling (NATPS), a novel computational method for simulating rare nonadiabatic events in photochemistry. NATPS efficiently generates reactive trajectories, reducing computational cost for studying excited-state dynamics.

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Last Updated: May 15, 2026

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Published on: December 2, 2016

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10:22

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Published on: June 16, 2014

Area of Science:

  • Computational Chemistry
  • Photochemistry
  • Quantum Dynamics

Background:

  • Nonadiabatic events are crucial in photochemistry but challenging to simulate due to computational demands and stochasticity.
  • Existing methods for simulating excited-state dynamics often struggle with efficiency and accuracy for rare events.

Purpose of the Study:

  • To introduce a deterministic and time-reversible method for simulating nonadiabatic dynamics.
  • To enable the application of transition path sampling (TPS) to excited-state processes.
  • To develop a new computational approach for studying rare nonadiabatic events.

Main Methods:

  • Developed a deterministic and time-reversible implementation of nonadiabatic dynamics based on the Mapping Approach to Surface Hopping (MASH).
  • Integrated MASH with the Transition Path Sampling (TPS) framework to create Nonadiabatic Transition Path Sampling (NATPS).
  • Established conditions for path ensemble sampling, including time reversibility and detailed balance.

Main Results:

  • NATPS efficiently generates ensembles of reactive trajectories for electronically coupled potential energy surfaces.
  • The method provides mechanistic insights into nonadiabatic pathways.
  • Significantly reduced computational effort compared to brute-force simulations and forward-flux sampling.

Conclusions:

  • NATPS offers a powerful and efficient approach for studying nonadiabatic dynamics in photochemistry.
  • This method facilitates the investigation of rare events in excited-state processes.
  • NATPS enhances our ability to understand complex photochemical mechanisms computationally.