paper

Beyond Flory theory: Distribution functions for interacting lattice trees

arXiv:1610.05230 · doi:10.1103/PhysRevE.95.012117

Abstract

While Flory theories provide an extremely useful framework for understanding the behavior of interacting, randomly branching polymers, the approach is inherently limited. Here we use a combination of scaling arguments and computer simulations to go beyond a Gaussian description. We analyse distributions functions for a wide variety of quantities characterising the tree connectivities and conformations for the four different statistical ensembles, which we have studied numerically in [Rosa and Everaers, J. Phys. A (2016, published) and J. Chem. Phys. (2016, to appear)]: (a) ideal randomly branching polymers, (b) and melts of interacting randomly branching polymers, (c) self-avoiding trees with annealed connectivity and (d) self-avoiding trees with quenched ideal connectivity. In particular, we investigate the distributions (i) of the weight, , of branches cut from trees of mass by severing randomly chosen bonds; (ii) of the contour distances, , between monomers; (iii) of spatial distances, , between monomers, and (iv) of the end-to-end distance of paths of length . Data for different tree sizes superimpose, when expressed as functions of suitably rescaled observables or . In particular, we observe a generalised Kramers relation for the branch weight distributions (i) and find that all the other distributions (ii-iv) are of Redner-des Cloizeaux type, . We propose a coherent framework, including generalised Fisher-Pincus relations, relating most of the RdC exponents to each other and to the contact and Flory exponents for interacting trees.

19 pages, 6 figures (including supplemental material). Submitted for publication

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Beyond Flory theory: Distribution functions for interacting lattice trees · wovepaper