Assessing the performance of coupled-trajectory schemes on full-dimensional two-state linear vibronic coupling models

Area of Science:

• Computational chemistry
• Quantum dynamics
• Photochemistry

Background:

• Nonadiabatic molecular dynamics simulations are crucial for understanding photochemical processes.
• Coupled-trajectory methods offer a potential improvement over independent-trajectory approaches.
• Accurate simulation of excited-state dynamics requires robust theoretical frameworks.

Purpose of the Study:

• To evaluate the performance of coupled-trajectory methods for simulating the photodynamics of DMABN and fulvene.
• To compare the coupled-trajectory Tully surface hopping (CCTTSH) and coupled-trajectory mixed quantum-classical (CTMQC) algorithms against independent-trajectory methods.
• To identify strengths and weaknesses of these methods in regions of strong nonadiabaticity.

Main Methods:

• Simulations of 4-(dimethylamino)benzonitrile (DMABN) and fulvene photodynamics.
• Application of linear vibrational coupling models for electronic structure.
• Comparison of coupled-trajectory mixed quantum-classical (CTMQC) and combined coupled-trajectory Tully surface hopping (CCTTSH) algorithms.
• Analysis of electronic populations and nuclear properties in position and momentum space.

Main Results:

• The CCTTSH algorithm successfully addresses internal inconsistencies found in previous coupled-trajectory Tully surface hopping methods.
• DMABN simulations reveal a significant limitation of the CTMQC algorithm when trajectories linger in strongly nonadiabatic regions.
• Both DMABN and fulvene exhibit distinct behaviors under the tested simulation methods.

Conclusions:

• The CCTTSH algorithm represents a significant advancement for coupled-trajectory surface hopping methods.
• The CTMQC method shows limitations in simulating systems with prolonged interactions in regions of strong nonadiabaticity.
• Careful selection of simulation methods is essential for accurate photodynamic studies, particularly in complex systems.