Answers are grounded in this paper and cite their sources.
The authors introduce a new Monte Carlo method to study random chains. The method uses (i) a link by link growth procedure of the chain, (ii) a chain replication procedure based on Boltzmann weights. They apply it to various cases in two and three dimensions (pure self-avoiding walk, repulsion between nearest-neighbour links and attraction between the chain extremities, etc.). When the competition (or frustration) between the different interaction terms increases, the chain may get trapped in local minima: to overcome this problem, they introduce a guiding field (or potential) ( phi i(r)). Step (ii) is now performed in the presence of this guiding field, which makes the chain population temporarily non-Boltzmannian. However, when the chain is completed, the final population obeys again the Boltzmann law. They study simple cases, where ( phi i(r)) may be chosen on physical grounds.
No takes yet. Share an insight, caveat, or question.
Garel et al. (1990) studied this question.
Synapse has enriched 10 related papers. Consider them for comparative context: