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Monte Carlo Simulation of the Θ-Point in Lattice Trees

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Numerical Methods for Polymeric Systems

Part of the book series: The IMA Volumes in Mathematics and its Applications ((IMA,volume 102))

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Abstract

Branched Polymers in solution are known to undergo a collapse transition driven by the quality of the solvent at the Θ-point. The collapse of the polymer is in a characteristic length, usually taken to be the root mean square radius of gyration, R, of the polymer. In the “good solvent” regime, one expects that R ~ M ν, where M is the molecular mass of the polymer. ν is a critical exponent, commonly called the metric exponent (and it describes the scaling of R with M). In three dimensions, it is believed that \(\nu = \tfrac{1}{2}\), and the branched polymer is said to be “expanded”. Beyond the collapse transition, it is believed that \(v = \frac{1}{2} \) , so that the polymer scales like a solid object (d is the spatial dimension). Branched polymers can be modeled as trees in the cubic lattice, with a short-ranged interaction between vertices which are nearest neighbour in the lattice. Trees can be efficiently sampled by a Metropolis Monte Carlo algorithm. We collect data on the Θ-transition by finding the peak in the specific heat of trees using a Robbins-Monro scheme. In addition, Monte Carlo simulations on trees over a wide range of the short-ranged force using umbrella sampling is described. The data strongly support the notion that the collapse transition is a continuous (second order) transition with a divergent specific heat. We also report values of computed critical exponents.

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© 1998 Springer Science+Business Media New York

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Van Rensburg, E.J.J., Madras, N. (1998). Monte Carlo Simulation of the Θ-Point in Lattice Trees. In: Whittington, S.G. (eds) Numerical Methods for Polymeric Systems. The IMA Volumes in Mathematics and its Applications, vol 102. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-1704-6_9

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  • DOI: https://doi.org/10.1007/978-1-4612-1704-6_9

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4612-7249-6

  • Online ISBN: 978-1-4612-1704-6

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