An algorithm based on Wang-Landau sampling for finding the global minimum of atomic clusters

In this work we present an algorithm for finding the global minimum of the energy in atomic clusters. The proposed algorithm combines the Monte-Carlo Wang-Landau random walk, local minimizations and heuristic moves of the energetic surface atoms. We test the algorithm with the optimizations of Lennard-Jones clusters. The algorithm is able to obtain each one of the global energy minima that are reported for Lennard-Jones clusters between 2 and 150 atoms.