A pivot algorithm for the location of a global minimum of a multiple-minimum problem is presented. The pivot method uses a series of randomly placed probes in phase space, moving the worst probes to be near better probes iteratively until the system converges. The approach chooses nearest-neighbor pivot probes to search the entire phase space by using a nonlocal distribution for the placement of the relocated probes. To test the algorithm, a standard suite of functions is given, as well as the energies and geometric structures of Lennard-Jones clusters, demonstrating the extreme efficiency of the method. Significant improvement over previous methods for high-dimensional systems is shown.
|Number of pages||4|
|Journal||Physical Review E - Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics|
|Publication status||Published - 1 Jan 1997|
ASJC Scopus subject areas
- Statistical and Nonlinear Physics
- Statistics and Probability
- Condensed Matter Physics