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. 2013 Sep 11;8(9):e74261. doi: 10.1371/journal.pone.0074261

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© 2013 Schöneberg, Noé

This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.

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Inline graphic — A: Dependency of the computed radial distribution function for different time step lengths . The black line shows the exact of -particles computed by Monte Carlo. The interaction potential was chosen to be a softcore repulsion potential () when their distance is closer than the sum of their collision radii . The colored lines show ’s computed from time discretized Brownian dynamics simulations with different timesteps. B: Root mean square error of the difference between Monte Carlo derived g(r) and the discretized diffusion simulation (displayed in same color code as A).

A: Dependency of the computed radial distribution function for different time step lengths . The black line shows the exact of -particles computed by Monte Carlo. The interaction potential was chosen to be a softcore repulsion potential () when their distance is closer than the sum of their collision radii . The colored lines show ’s computed from time discretized Brownian dynamics simulations with different timesteps. B: Root mean square error of the difference between Monte Carlo derived g(r) and the discretized diffusion simulation (displayed in same color code as A).