Self - Avoiding Random Surfaces : Monte Carlo Study using Oct - tree Data
نویسندگان
چکیده
Self-avoiding random surfaces on a cubic lattice are studied by extensive Monte Carlo sampling. The surfaces have empty boundary and the topology of a 2-sphere. An oct-tree data-structure allows to obtain good statistics for surfaces whose plaquette number is almost an order of magnitude greater than in previous investigations. Maximum likelihood determinations of the critical plaquette fugacity, ?1 , and entropic exponent, , can be extrapolated to the estimates: = , and =. The linear regression estimate for the radius of gyration exponent is =. The results support a location of the problem within the branched polymers universality class.
منابع مشابه
Self Avoiding Random Surfaces
Self avoiding random surfaces on a cubic lattice are studied by extensive Monte Carlo sampling The surfaces have empty boundary and the topology of a sphere An oct tree data structure allows to obtain good statistics for surfaces whose plaquette number is almost an order of magnitude greater than in previous investigations Maximum likelihood determinations of the critical plaquette fugacity and...
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