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Trajectory surface hopping within linear response time-dependent density-functional theory.

Enrico Tapavicza1, Ivano Tavernelli, Ursula Rothlisberger

  • 1Laboratory of Computational Chemistry and Biochemistry, Ecole Polytechnique Fédérale de Lausanne.

Physical Review Letters
|March 16, 2007
PubMed
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A new fewest switches algorithm for trajectory surface hopping was developed. This method accurately models excited-state dynamics in molecules like protonated formaldimine, crucial for understanding vision.

Area of Science:

  • Computational Chemistry
  • Quantum Chemistry
  • Photochemistry

Background:

  • Understanding excited-state dynamics is crucial for photochemistry.
  • Accurate modeling of nonadiabatic processes is computationally challenging.
  • Protonated formaldimine serves as a model for retinal, the chromophore in rhodopsin.

Purpose of the Study:

  • To develop and implement a novel fewest switches trajectory surface hopping algorithm.
  • To introduce a method for calculating nonadiabatic couplings using a multi-determinantal approximation.
  • To apply the new method to study the photorelaxation dynamics of protonated formaldimine.

Main Methods:

  • Linear response time-dependent density-functional theory (LR-TDDFT).
  • Fewest switches trajectory surface hopping algorithm.

Related Experiment Videos

  • Ab initio molecular dynamics (AIMD) using the CPMD package.
  • Multi-determinantal approximation for excited state wave functions.

    • Main Results:

    • The developed algorithm was successfully implemented in the CPMD package.
    • A scheme for calculating nonadiabatic couplings was introduced and applied.
    • The method was used to study the photorelaxation of protonated formaldimine.
    • Results showed good agreement with established methods like state-averaged multiconfiguration self-consistent field (SA-MCSCF).

    Conclusions:

    • The new fewest switches algorithm provides an accurate and efficient approach for studying excited-state dynamics.
    • The method is suitable for modeling photorelaxation processes in complex molecular systems.
    • This work advances the computational study of photochemical reactions and vision mechanisms.