Most recent works on Brownian dynamics simulation employ a first‐order algorithm developed by Ermak and McCammon [J. Chem. Phys. 69, 1352 (1978)]. In this work we propose the use of a second‐order algorithm in which the step is a combination of two first‐order steps, like in the second‐order Runge–Kutta method for differential equations. Although the computer time per step is roughly doubled, the second‐order algorithm is more efficient than the previous one because a given accuracy in the results can be achieved with less than half the number of steps. The new algorithm also allows for longer time steps without divergence. The advantage of the new procedure is illustrated in the simulation of four macromolecular systems: A quasirigid dumbbell, a semiflexible trumbbell, a semiflexible hinged rod, and a Gaussian polymer chain.
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1 February 1990
Research Article|
February 01 1990
A second‐order algorithm for the simulation of the Brownian dynamics of macromolecular models
A. Iniesta;
A. Iniesta
Departamento de Química Física, Facultad de Ciencias Químicas y Matemáticas, Universidad de Murcia, 30100 Murcia, Spain
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J. García de la Torre
J. García de la Torre
Departamento de Química Física, Facultad de Ciencias Químicas y Matemáticas, Universidad de Murcia, 30100 Murcia, Spain
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J. Chem. Phys. 92, 2015–2018 (1990)
Article history
Received:
June 12 1989
Accepted:
September 19 1989
Citation
A. Iniesta, J. García de la Torre; A second‐order algorithm for the simulation of the Brownian dynamics of macromolecular models. J. Chem. Phys. 1 February 1990; 92 (3): 2015–2018. https://doi.org/10.1063/1.458034
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