English

Reduced-variance orientational distribution functions from torque sampling

Soft Condensed Matter 2023-04-12 v2 Statistical Mechanics Computational Physics Data Analysis, Statistics and Probability

Abstract

We introduce a method to sample the orientational distribution function in computer simulations. The method is based on the exact torque balance equation for classical many-body systems of interacting anisotropic particles in equilibrium. Instead of the traditional counting of events, we reconstruct the orientational distribution function via an orientational integral of the torque acting on the particles. We test the torque sampling method in two- and three-dimensions, using both Langevin dynamics and overdamped Brownian dynamics, and with two interparticle interaction potentials. In all cases the torque sampling method produces profiles of the orientational distribution function with better accuracy than those obtained with the traditional counting method. The accuracy of the torque sampling method is independent of the bin size, and hence it is possible to resolve the orientational distribution function with arbitrarily small angular resolutions.

Keywords

Cite

@article{arxiv.2212.11576,
  title  = {Reduced-variance orientational distribution functions from torque sampling},
  author = {Johannes Renner and Matthias Schmidt and Daniel de las Heras},
  journal= {arXiv preprint arXiv:2212.11576},
  year   = {2023}
}
R2 v1 2026-06-28T07:48:26.500Z