caa a22 4500 445391146 CHVBK 20180317143047.0 cr unu---uuuuu 170323e20110801xx s 000 0 eng 10.1007/s10955-011-0268-x doi (NATIONALLICENCE)springer-10.1007/s10955-011-0268-x A Review of Monte Carlo Simulations of Polymers with PERM [Elektronische Daten] [Hsiao-Ping Hsu, Peter Grassberger] In this review, we describe applications of the pruned-enriched Rosenbluth method (PERM), a sequential Monte Carlo algorithm with resampling, to various problems in polymer physics. PERM produces samples according to any given prescribed weight distribution, by growing configurations step by step with controlled bias, and correcting "bad” configurations by "population control”. The latter is implemented, in contrast to other population based algorithms like e.g. genetic algorithms, by depth-first recursion which avoids storing all members of the population at the same time in computer memory. The problems we discuss all concern single polymers (with one exception), but under various conditions: Homopolymers in good solvents and at the Θ point, semi-stiff polymers, polymers in confining geometries, stretched polymers undergoing a forced globule-linear transition, star polymers, bottle brushes, lattice animals as a model for randomly branched polymers, DNA melting, and finally—as the only system at low temperatures, lattice heteropolymers as simple models for protein folding. PERM is for some of these problems the method of choice, but it can also fail. We discuss how to recognize when a result is reliable, and we discuss also some types of bias that can be crucial in guiding the growth into the right directions. Springer Science+Business Media, LLC, 2011 Polymers nationallicence Chain growth nationallicence Population control nationallicence Phase transitions nationallicence Lattice animals nationallicence Protein folding nationallicence Hsu Hsiao-Ping Institut für Physik, Johannes Gutenberg-Universität, 55099, Mainz, Germany aut Grassberger Peter Forschungszentrum Jülich, 52425, Jülich, Germany aut Journal of Statistical Physics Springer US; http://www.springer-ny.com 144/3(2011-08-01), 597-637 0022-4715 144:3<597 2011 144 10955 https://doi.org/10.1007/s10955-011-0268-x text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s10955-011-0268-x text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Hsu Hsiao-Ping Institut für Physik, Johannes Gutenberg-Universität, 55099, Mainz, Germany aut NATIONALLICENCE 700 1- Grassberger Peter Forschungszentrum Jülich, 52425, Jülich, Germany aut NATIONALLICENCE 773 0- Journal of Statistical Physics Springer US; http://www.springer-ny.com 144/3(2011-08-01), 597-637 0022-4715 144:3<597 2011 144 10955 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer