A discrete-continuous algorithm for molecular energy minimization

A parallel algorithm for minimizing molecular energy potential functions is applied to the case of pure Lennard-Jones (LJ) clusters. The algorithm demonstrates the combination of discrete, lattice-based optimization with continuous optimization (relaxation) techniques. The suggested approach is not restricted to the LJ potential and is aimed at problems in which the potential of interest may be significantly more costly than the LJ. The intended audience includes researchers interested in practical computational problems involving minimum energy cluster conformation, such as may arise in catalysis, and those interested in algorithm development. The advantage of the algorithm is that the time required to find the minimum-energy structure for a relatively large cluster reduces to that of an interactive session. The current parallel implementation is capable of determining the best-known previously published binding energies for n⩽150 LJ clusters in a matter of seconds and has provided new results on minimum energies for clusters of up to n=1000 atoms using a massively parallel processor, the CM-5