Recent advances in the Monte Carlo sampling of polymer configurations

I will discuss work in progress to extend the use of efficient data structures from lattice self-avoiding walks to the Monte Carlo sampling of configurations for other polymer models. In particular, I will discuss the sampling of dense polymer configurations (in fact, Hamiltonian paths) via so-called backbite moves, and the sampling of continuum polymers in the self-avoiding walk universality class via an efficient implementation of the pivot algorithm.Non UBCUnreviewedAuthor affiliation: Swinburne University of TechnologyResearche