flatIGW — An inverse algorithm to compute the density of states of lattice self avoiding walks

M. Ponmurugan, V. Sridhar, S.L. Narasimhan and K.P.N. Murthy

Physica A: Statistical Mechanics and its Applications, 2011, vol. 390, issue 7, 1258-1268

Abstract: We show that the Density of States (DoS) for lattice Self Avoiding Walks can be estimated by using an inverse algorithm, called flatIGW, whose step-growth rules are dynamically adjusted by requiring the energy histogram to be locally flat. Here, the (attractive) energy associated with a configuration is taken to be proportional to the number of non-bonded nearest neighbor pairs (contacts). The energy histogram is able to explicitly direct the growth of a walk because the step-growth rule of the Interacting Growth Walk (Narasimhan et al. (2003) [5]) samples the available nearest neighbor sites according to the number of contacts they would make. We have obtained the complex Fisher zeros corresponding to the DoS, estimated for square lattice walks of various lengths, and located the θ temperature by extrapolating the finite size values of the real zeros to their asymptotic value, ∼1.49 (reasonably close to the known value, ∼1.50 (Barkema et al. (1998) [14]).

Keywords: Self avoiding walk; Interacting Growth Walk; Density of states; Zeros of partition function; Energy histogram; Theta point; Monte Carlo simulation (search for similar items in EconPapers)
Date: 2011
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:390:y:2011:i:7:p:1258-1268

DOI: 10.1016/j.physa.2010.11.023

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