Analysis of sequential algorithms as tools for modeling the chain-like-body evolution

This presentation is devoted to the algorithmization of the chain-like body's movements. An ample set of experimental data and recent theoretical achievements show that chain-like polymers traversing a membrane opening undergo multiple changes of their shape. These changes are mostly due to a mechanical tension induced by an environment with its chemical interactions that affect polymer's mobility. Known analytical approaches yield qualitative description of chain-shape deformations whereas a quantitative insight mostly relies on numerical experiments. These experiments are conducted with the help of a Monte-Carlo-like class of algorithms to mimic evolutions of chain trajectory in the space. Obviously, an efficient generation of trajectories with high acceptance ratio is crucial. In this paper we focus on our algorithm employing sequentialization of the chain move into one-chain-segments steps. An image of sequentially decomposed chain's move used by us in the process of the trajectory reconstruction involves the tension propagation mechanism as well. The sequences of virtual chain-segment steps followed by the progressed tension are in the core of our sequential algorithm. In this paper we analyze this algorithm as a tool for mimicking the real polymer evolution. For this propose we compare our movement assumptions with these that are adopted in other algorithms employed in the polymer studies. In this context we also address some important physical features that should be manifested by any well simulated movement trajectory.