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Semiclassical Monte Carlo: a first principles approach to non-adiabatic molecular dynamics
Alexander J White1, Vyacheslav N Gorshkov1, Ruixi Wang1
1Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA.
This study introduces a new quantum chemistry algorithm for modeling molecular dynamics, accurately simulating complex photophysical processes using semiclassical surface hopping. The method offers a cost-effective and improvable approach for large systems.
Area of Science:
- Quantum chemistry
- Theoretical chemistry
- Computational chemistry
Background:
- Modeling photophysical and photochemical reactions in large molecular systems is challenging.
- Existing methods for non-adiabatic dynamics are often computationally expensive or rely on approximations.
- Accurate simulation requires incorporating electronic state transitions and quantum coherence effects.
Purpose of the Study:
- To present a novel algorithm for simulating non-adiabatic dynamics in extended molecular systems.
- To provide a cost-effective and systematically improvable method for quantum chemistry.
- To achieve excellent agreement with exact quantum mechanical results.
Main Methods:
- Monte Carlo sampling of the semiclassical time-dependent wavefunction.
- Surface hopping dynamics simulation.
- Post-processing step for enhanced accuracy.
Main Results:
- The algorithm demonstrates excellent agreement with exact quantum mechanical solutions for scattering problems.
- Wavefunction convergence is influenced by complex-valued phase factors, non-adiabatic coupling region size, and sampling function choice.
- The method requires minimal input from quantum chemistry calculations and is computationally efficient.
Conclusions:
- The developed algorithm is a promising tool for simulating complex molecular dynamics in large systems.
- The findings provide insights into the method's applicability and suggest avenues for future improvements.
- This approach bridges the gap between accuracy and computational cost in quantum dynamics simulations.
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