Artificial Neural Networks as Propagators in Quantum Dynamics.
J Phys Chem Lett
; 12(43): 10654-10662, 2021 Nov 04.
Article
em En
| MEDLINE
| ID: mdl-34704767
ABSTRACT
The utilization of artificial neural networks (ANNs) provides strategies for accelerating molecular simulations. Herein, ANNs are implemented as propagators of the time-dependent Schrödinger equation to simulate the quantum dynamics of systems with time-dependent potentials. These ANN propagators are trained to map nonstationary wavepackets from a given time to a future time within the discrete variable representation. Each propagator is trained for a specified time step, and iterative application of the propagator enables the propagation of wavepackets over long time scales. Such ANN propagators are developed and applied to one- and two-dimensional proton transfer systems, which exhibit nuclear quantum effects such as hydrogen tunneling. These ANN propagators are trained for either a specific time-independent potential or general potentials that can be time-dependent. Hierarchical, multiple time step algorithms enable parallelization, and the extension to higher dimensions is straightforward. This strategy is applicable to quantum dynamical simulations of diverse chemical and biological processes.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Teoria Quântica
/
Redes Neurais de Computação
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Simulação de Dinâmica Molecular
Tipo de estudo:
Prognostic_studies
Idioma:
En
Ano de publicação:
2021
Tipo de documento:
Article