Global Optimization of Atomic Cluster Structures Using Parallel Genetic Algorithms

Abstract

The study of the structure and physical properties of atomic clusters is an extremely active area of research due to their importance, both in fundamental science and in applied technology. For medium size atomic clusters most of the structures reported today have been obtained by local optimizations of plausible structures using DFT (Density Functional Theory) methods and/or by global optimizations in which much more approximate methods are used to calculate the cluster's energetics. Our previous work shows that these approaches can not be reliably used to study atomic cluster structures and that approaches based on global optimization schemes are needed. In this paper, we report the implementation and application of a parallel Genetic Algorithm (GA) to predict the structure of medium size atomic clusters.

Transition fromexotoendoCu absorption in CuSinclusters: a genetic algorithms density functional theory study

“…[32, 33] All the energy calculations were done using the CPMD code. [34] The isomers selected by MGAC/CPMD calculations were analyzed, and their vibration frequencies evaluated to discriminate transition states (TS) from stable structures.…”

Digital Sherpa

“…As discussed above, MGAC is a compute intensive implementation of a GA method for structure prediction of organic crystals and atomic clusters [9][10][11][12][13][14][15]. MGAC was implemented using MPI and C++ and it was designed to run on tightly coupled cluster of processors.…”

“…Finally, as an example we describe how we have implemented a new grid enabled version of the MGAC (Modified Genetic Algorithms for Crystal and Clusters) program [9][10][11][12][13][14][15] (MGAC-CGA). MGAC is a system of programs for crystal and atomic cluster structure prediction based on Genetic Algorithms (GA), that requires large amounts of computer time and that was designed with a particular emphasis in exploiting the natural parallelism existing in GA.…”