MGAC MODIFIED GENETIC ALGORITHM FOR CRYSTALS AND CLUSTERS

MGAC (MODIFIED GENETIC ALGORITHM FOR CRYSTALS AND CLUSTERS): PREDICTION OF FLEXIBLE MOLECULES. Ferraro, M 1, Facelli, J. 2, Bazterra V. 1, 2 1 Dpto de Física, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires. (1428) Ciudad Universitaria, Pab. I, Bs. As. 2 Center for High Performance Computing, University of Utah, 155 S 1452 E RM 405, Salt Lake City, UT 84112 -0190, USA, . In this presentation we describe a new distributed computing framework for crystal structure prediction that is capable of performing crystal structures searches for flexible molecules within any space group and within an arbitrary number of molecules in the asymmetric unit. The crystal structure prediction (CSP) of organic compounds can be described as the process of creating a list of crystal structure candidates, which are likely to be found experimentally, using only the molecular composition and connectivity as input information. Genetic Algorithms (GAs) are a family of search techniques rooted on the ideas of Darwinian evolution. [1] Operators analogue to crossover, mutation and natural selection are employed to perform a search able to explore and learn the multidimensional parameter space and determine which regions of the space provide good solutions to a problem. To improve their convergence GAs are commonly coupled with local optimizations at each generation. This combined approach has been implemented in our program MGAC (Modified Genetic Algorithm for Crystal and Clusters). [2] ACRY 02 - Pbca Alpyph (P 21/c) 1 - D. E. Goldberg, Genetic Algorithms in Search, Optimisation and Machine Learning (Addison-Wesley, New York, 1989). 2 - V. E. Bazterra, M. B. Ferraro, and J. C. Facelli, Int. J. Quantum Chem. 96, (2004) 312 and references therein. 3 - A. D. Mac. Kerell, J. Brooks, B. , C. L. Brooks III, et al. , in The Encyclopedia of Computational Chemistry, edited by P. v. R. S. e. al. (John Wiley & Sons, Chichester, 1998), p. 271. Crystal structure coding