Living Journal of Computational Molecular Science · 2018 · 177 citations · 37 references
Natural SciencesChemistryPhysicsComputational ChemistryComputational PhysicsUncertainty QuantificationComputational ModelingMolecular DynamicsMolecular ModelingMolecular SimulationSimulation MethodsUncertainty AnalysisEnhanced SamplingMolecular Dynamics SamplingMolecular Dynamics Trajectory AnalysisMolecular Simulation AnalysisSampling Data QualitySystematic ErrorsSystematic UncertaintiesTrajectory Data Quality Assessment
The quantitative assessment of uncertainty and sampling quality is essential in molecular simulation. Many systems of interest are highly complex, often at the edge of current computational capabilities. Modelers must therefore analyze and communicate statistical uncertainties so that "consumers'' of simulated data understand its significance and limitations. This article covers key analyses appropriate for trajectory data generated by conventional simulation methods such as molecular dynamics and (single Markov chain) Monte Carlo. It also provides guidance for analyzing some "enhanced" sampling approaches. We do not discuss systematic errors arising, e.g., from inaccuracy in the chosen model or force field.
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