Two-dimensional lattice polymers: Adaptive windows simulations

Cunha-Netto, A. G.; Dickman, Ronald; Caparica, A. A.

doi:10.1016/j.cpc.2008.12.015

Cited by 18 publications

(13 citation statements)

References 33 publications

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“…As a new application of the criterion, we consider a homopolymer consisting of N monomers which may assume any self avoiding walk (SAW) configuration on a two-dimensional lattice [19,20]. Assuming that the polymer is in a bad solvent, there is an effective monomermonomer attraction in addition to the self-avoidance constraint representing excluded volume.…”

Section: Homopolymermentioning

confidence: 99%

Wang-Landau sampling: A criterion for halting the simulations

Caparica

2014

Phys. Rev. E

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In this work we propose a criterion to finish the simulations of the Wang-Landau sampling. Instead of determining a final modification factor for all simulations and every sample sizes, we investigate the behavior of the temperature of the peak of the specific heat during the simulations and finish them when this value varies bellow a given limit. As a result, different runs stop at different final modification factors. We show that in place of the temperature of the peak of the specific heat one can adopt alternatively the integrated heat transfer as a reference quantity. We apply this technique to the two-dimensional Ising model and a homopolymer. We verify that for the Ising model the mean order of the final modification factors are roughly the same for all lattice sizes, but for the homopolymer the order of the final modification factors increases with increasing polymer sizes. The results show that the simulations can be halted much earlier then it is conventional in Wang-Landau sampling, but manifold finite-size simulations are required in order to obtain accurate results. A brief application to the three-dimensional Ising model is also available.

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Section: Homopolymermentioning

confidence: 99%

Wang-Landau sampling: A criterion for halting the simulations

Caparica

2014

Phys. Rev. E

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“…On the other hand, Schulz et al [12] found it advantageous to introduce an additional rule, namely, whenever a configuration is rejected because its energy is greater than the maximum value, E > , of a given window, one should update g(E) for the current energy value. These prescriptions are effective for Ising models but do not eliminate boundary effects in all instances, e.g., in simulations of polymers [13] and systems where the JDOS is required [14].…”

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confidence: 99%

Improving Wang-Landau sampling with adaptive windows

et al. 2008

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Wang-Landau sampling (WLS) of large systems requires dividing the energy range into "windows" and joining the results of simulations in each window. The resulting density of states (and associated thermodynamic functions) are shown to suffer from boundary effects in simulations of lattice polymers and the five-state Potts model. Here, we implement WLS using adaptive windows.Instead of defining fixed energy windows (or windows in the energy-magnetization plane for the Potts model), the boundary positions depend on the set of energy values on which the histogram is flat at a given stage of the simulation. Shifting the windows each time the modification factor f is reduced, we eliminate border effects that arise in simulations using fixed windows. Adaptive windows extend significantly the range of system sizes that may be studied reliably using WLS.

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“…These difficulties have been overcome by the development of alternative MC methods, such as paralleltempering [16], cluster algorithms [17], multicanonical algorithms [18], and more recently the Wang-Landau method [19]. This method has been applied with great success to many systems, in particular to polymers in lattice [20][21][22].…”

Section: Introductionmentioning

confidence: 98%