ON MONTE-CARLO AND MOLECULAR-DYNAMICS METHODS INSPIRED BY TSALLIS STATISTICS - METHODOLOGY, OPTIMIZATION, AND APPLICATION TO ATOMIC CLUSTERS

Generalized Monte Carlo and molecular dynamics algorithms which provid e enhanced sampling of the phase space in the calculation of equilibri um thermodynamic properties is presented. The algorithm samples trial moves from a generalized statistical distribution derived from a modif ication of the Gibbs-Shannon entropy proposed by Tsallis. Results for a one-dimensional model potential demonstrate that the algorithm leads to a greatly enhanced rate of barrier crossing and convergence in the calculation of equilibrium averages. Comparison is made with standard Metropolis Monte Carlo and the J-walking algorithm of Franz, Freeman and Doll. Application to a 13-atom Lennard-Jones cluster demonstrates the ease with which the algorithm may be applied to complex molecular systems. (C) 1997 American Institute of Physics.