Exploration versus Exploitation in Global Atomistic Structure Optimization
The ability to navigate vast energy landscapes of molecules, clusters, and solids is a necessity for discovering novel compounds in computational chemistry and materials science. For high-dimensional systems, it is only computationally feasible to search a small portion of the landscape, and hence,...
Saved in:
Published in | The journal of physical chemistry. A, Molecules, spectroscopy, kinetics, environment, & general theory Vol. 122; no. 5; pp. 1504 - 1509 |
---|---|
Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
United States
American Chemical Society
08.02.2018
|
Online Access | Get full text |
Cover
Loading…
Summary: | The ability to navigate vast energy landscapes of molecules, clusters, and solids is a necessity for discovering novel compounds in computational chemistry and materials science. For high-dimensional systems, it is only computationally feasible to search a small portion of the landscape, and hence, the search strategy is of critical importance. Introducing Bayesian optimization concepts in an evolutionary algorithm framework, we quantify the concepts of exploration and exploitation in global minimum searches. The method allows us to control the balance between probing unknown regions of the landscape (exploration) and investigating further regions of the landscape known to have low-energy structures (exploitation). The search for global minima structures proves significantly faster with the optimal balance for three test systems (molecular compounds) and to a lesser extent also for a crystalline surface reconstruction. In addition, global search behaviors are analyzed to provide reasonable grounds for an optimal balance for different problems. |
---|---|
Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 1089-5639 1520-5215 |
DOI: | 10.1021/acs.jpca.8b00160 |