Constructing Grids for Molecular Quantum Dynamics Using an Autoencoder

Zauleck, Julius P. P. und Vivie-Riedle, Regina de (2018): Constructing Grids for Molecular Quantum Dynamics Using an Autoencoder. In: Journal of Chemical Theory and Computation, Bd. 14, Nr. 1: S. 55-62

Abstract

A challenge for molecular quantum dynamics (QD) calculations is the curse of dimensionality with respect to the nuclear degrees of freedom. A common approach that works especially well for fast reactive processes is to reduce the dimensionality of the system to a few most relevant coordinates. Identifying these can become a very difficult task, because they often are highly unintuitive. We present a machine learning approach that utilizes an autoencoder that is trained to find a low-dimensional representation of a set of molecular configurations. These configurations are generated by trajectory calculations performed on the reactive molecular systems of interest. The resulting low-dimensional representation can be used to generate a potential energy surface grid in the desired subspace. Using the G-matrix formalism to calculate the kinetic energy operator, QD calculations can be carried out on this grid. In addition to step-by-step instructions for the grid construction, we present the application to a test system.

• Dokumententyp: Zeitschriftenartikel
• Fakultät: Chemie und Pharmazie > Department Chemie
• Themengebiete: 500 Naturwissenschaften und Mathematik > 540 Chemie
• ISSN: 1549-9618
• Sprache: Englisch