A Breadth‐First Pruned‐Enriched Rosenbluth Method for Force–Extension Simulations of Confined Semiflexible Chains

Semiflexible polymers exhibit rich mechanical responses to external fields. Such behavior underpins processes ranging from genome organization to nanofluidic manipulation. As a versatile numerical approach, Monte Carlo simulation enables quantitative studies of polymer mechanics in complex microenvironments. Therefore, efficient sampling of systems involving coupled effects, such as spatial confinement and an external force, remains of practical interest. Here, building on the Pruned‐enriched Rosenbluth method, we propose a new sampling framework that combines adaptive weight control with a breadth‐first chain‐growth strategy. The method advances chain growth synchronously while maintaining a fixed population size. By using the average weight as an adaptive reference, resampling is performed without introducing additional tuning parameters. As an application, we investigate the statistical mechanics of stretched wormlike chains confined in elliptical nanochannels and, more generally, in two‐parameter cross‐sectional tubes. Their cross‐sectional dimensions are specified by two independent length parameters. Following the technical route by treating tube confinement as the equivalent force, we obtain a closed‐form expression for the force–extension relation and validate it through systematic simulations.