Block Covariance Overlap Method and Convergence in Molecular Dynamics Simulation

Molecular dynamics (MD) is a powerful tool for understanding the fluctuations of biomolecular systems. It is, however, subject to statistical errors in its sampling of the underlying distribution of states. One must understand these errors in order to draw meaningful conclusions from the simulation. This is becoming ever more critical as MD simulations of even larger systems are attempted. We present here a new method for determining the extent of convergence that relies on measures of the fluctuation space sampled by the simulation without any a priori knowledge of states or partitioning of the configuration space. This method reveals long correlation times, even for simple systems, and suggests caution when interpreting macromolecular simulations. We also compare this method with previous efforts to characterize the sampling of MD simulation.