2008 J. Phys.: Condens. Matter 20 304201 (9pp) doi: 10.1088/0953-8984/20/30/304201
1 Instituto de Ciencia de Materiales (CSIC), Cantoblanco, 28049 Madrid, Spain
2 Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, UK
3 Lehrstuhl für Festkörperphysik, Universität Erlangen-Nürnberg, Staudtstrasse 7, 91058 Erlangen, Germany
Abstract. The performance of a combinatorial simultaneous optimization (SO) algorithm is tested using experimental LEED I(E) data from Cu(100) and Fe0.57Al0.47(100) surfaces. SO optimizes structures taking advantage of the experimental database at two levels: (i) commensurate subsets of the database with the number of unknown parameters are chosen to find local solutions using Broyden's method and (ii) these partial structural solutions are used to build a Markov chain over the whole database. This procedure is of global character, the same as simulated annealing or genetic algorithm methods, but displays a very competitive scaling law because after the first iteration candidates are not chosen by a blind/random pick; they are already solutions to the problem with a restricted experimental database.