Wang-Landau and Stochastic Approximation Monte Carlo for Semi-flexible Polymer Chains

Werlich, B.; Taylor, Mark P.; Paul, Wolfgang

doi:10.1016/j.phpro.2014.08.137

Cited by 6 publications

(1 citation statement)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Very recently a new version of the WL algorithm, the Stochastic Approximation Monte Carlo [34,35], which uses the 1/t strategy has been successfully applied to semi-flexible polymers chains.…”

Section: Introductionmentioning

confidence: 99%

Nonconvergence of the Wang-Landau algorithms with multiple random walkers

Belardinelli

Pereyra

2016

Phys. Rev. E

View full text Add to dashboard Cite

This paper discusses some convergence properties in the entropic sampling Monte Carlo methods with multiple random walkers, particularly in the Wang-Landau (WL) and 1/t algorithms. The classical algorithms are modified by the use of m independent random walkers in the energy landscape to calculate the density of states (DOS). The Ising model is used to show the convergence properties in the calculation of the DOS, as well as the critical temperature, while the calculation of the number π by multiple dimensional integration is used in the continuum approximation. In each case, the error is obtained separately for each walker at a fixed time, t; then, the average over m walkers is performed. It is observed that the error goes as 1/ √ m. However, if the number of walkers increases above a certain critical value m > mx, the error reaches a constant value (i.e. it saturates). This occurs for both algorithms; however, it is shown that for a given system, the 1/t algorithm is more efficient and accurate than the similar version of the WL algorithm. It follows that it makes no sense to increase the number of walkers above a critical value mx, since it does not reduces the error in the calculation. Therefore, the number of walkers does not guarantee convergence.

show abstract

Section: Introductionmentioning

confidence: 99%

Nonconvergence of the Wang-Landau algorithms with multiple random walkers

Belardinelli

Pereyra

2016

Phys. Rev. E

View full text Add to dashboard Cite

show abstract

Stochastic approximation Monte Carlo and Wang–Landau Monte Carlo applied to a continuum polymer model

Werlich

Shakirov

Taylor

et al. 2015

Computer Physics Communications

View full text Add to dashboard Cite

Diagram of states and morphologies of flexible-semiflexible copolymer chains: A Monte Carlo simulation

Zablotskiy

Martemyanova

Иванов

et al. 2016

The Journal of Chemical Physics

View full text Add to dashboard Cite

A single copolymer chain consisting of multiple flexible (F) and semiflexible (S) blocks has been studied using a continuum bead-spring model by Stochastic Approximation Monte Carlo simulations, which determine the density of states of the model. The only difference between F and S blocks is the intramolecular bending potential, all non-bonded interactions are equal. The state diagrams for this class of models display multiple nematic phases in the collapsed state, characterized through a demixing of the blocks of different stiffness and orientational ordering of the stiff blocks. We observe dumbbell-like morphologies, lamellar phases, and for the larger block lengths also Saturn-like structures with a core of flexible segments and the stiff segments forming a ring around the core.

show abstract

Wang-Landau and Stochastic Approximation Monte Carlo for Semi-flexible Polymer Chains

Abstract: We present a comparison of the performance, relative strengths and relative weaknesses of standard Wang-Landau Monte Carlo simulations and Stochastic Approximation Monte Carlo simulations applied to semi-flexible single polymer chains.

Cited by 6 publications

References 20 publications

Nonconvergence of the Wang-Landau algorithms with multiple random walkers

Nonconvergence of the Wang-Landau algorithms with multiple random walkers

Stochastic approximation Monte Carlo and Wang–Landau Monte Carlo applied to a continuum polymer model

Diagram of states and morphologies of flexible-semiflexible copolymer chains: A Monte Carlo simulation

Contact Info

Product

Resources

About