Two improved versions of the pruned-enriched-Rosenbluth method (PERM) are
proposed and tested on simple models of lattice heteropolymers. Both are found
to outperform not only the previous version of PERM, but also all other
stochastic algorithms which have been employed on this problem, except for the
core directed chain growth method (CG) of Beutler & Dill. In nearly all test
cases they are faster in finding low-energy states, and in many cases they
found new lowest energy states missed in previous papers. The CG method is
superior to our method in some cases, but less efficient in others. On the
other hand, the CG method uses heavily heuristics based on presumptions about
the hydrophobic core and does not give thermodynamic properties, while the
present method is a fully blind general purpose algorithm giving correct
Boltzmann-Gibbs weights, and can be applied in principle to any stochastic
sampling problem.Comment: 9 pages, 9 figures. J. Chem. Phys., in pres