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High-order geometric integrators for the variational Gaussian approximation
Roya Moghaddasi Fereidani1, Jiří J L Vaníček1
1Laboratory of Theoretical Physical Chemistry, Institut des Sciences et Ingénierie Chimiques, Ecole Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland.
High-order geometric integrators improve the efficiency of the accurate variational Gaussian approximation for quantum dynamics. This method conserves energy and the symplectic structure, offering a significant speedup for complex systems.
Area of Science:
- Quantum mechanics
- Computational chemistry
- Theoretical physics
Background:
- The time-dependent Schrödinger equation (TDSE) governs quantum system evolution.
- Gaussian-based methods offer approximations for solving the TDSE.
- The variational Gaussian approximation (VGA) is accurate but computationally expensive.
Purpose of the Study:
- To enhance the efficiency of the variational Gaussian approximation (VGA).
- To develop high-order geometric integrators for quantum dynamics simulations.
- To assess the performance of these integrators on complex, high-dimensional systems.
Main Methods:
- Symmetric composition of a second-order symplectic integrator (Faou-Lubich).
- Development of arbitrary even-order geometric integrators.
- Application to a twenty-dimensional model of coupled Morse oscillators.
Main Results:
- High-order integrators drastically speed up convergence compared to second-order methods.
- The developed integrators are time-reversible and conserve norm and symplectic structure exactly.
- The variational method, enhanced by these integrators, captures tunneling and improves accuracy over the thawed Gaussian approximation.
Conclusions:
- The developed high-order geometric integrators significantly improve the computational efficiency of the variational Gaussian approximation.
- This approach provides an accurate and stable method for simulating quantum dynamics, even in high-dimensional systems.
- The method offers advantages over traditional numerical techniques like the Runge-Kutta method.
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