pyMSER – An open-source library for automatic equilibration detection in molecular simulations
arxiv(2024)
摘要
Automated molecular simulations are used extensively for predicting material
properties. Typically, these simulations exhibit two regimes: a dynamic
equilibration part, followed by a steady state. For extracting observable
properties, the simulations must first reach a steady state so that
thermodynamic averages can be taken. However, as equilibration depends on
simulation conditions, predicting the optimal number of simulation steps a
priori is impossible. Here, we demonstrate the application of the Marginal
Standard Error Rule (MSER) for automatically identifying the optimal truncation
point in Grand Canonical Monte Carlo (GCMC) simulations. This novel automatic
procedure determines the point in which steady state is reached, ensuring that
figures-of-merits are extracted in an objective, accurate, and reproducible
fashion. In the case of GCMC simulations of gas adsorption in metal-organic
frameworks, we find that this methodology reduces the computational cost by up
to 90
creates the data, this library is, in principle, applicable to any time series
analysis in which equilibration truncation is required. The open-source Python
implementation of our method, pyMSER, is publicly available for reuse and
validation at https://github.com/IBM/pymser.
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