Error Assessment of Computational Models in Chemistry

Authors

  • Gregor N. Simm ETH Zürich Laboratorium für Physikalische Chemie Vladimir-Prelog-Weg 2, CH-8093 Zurich, Switzerland
  • Jonny Proppe ETH Zürich Laboratorium für Physikalische Chemie Vladimir-Prelog-Weg 2, CH-8093 Zurich, Switzerland
  • Markus Reiher ETH Zürich Laboratorium für Physikalische Chemie Vladimir-Prelog-Weg 2, CH-8093 Zurich, Switzerland. Markus.Reiher@phys.chem.ethz.ch

DOI:

https://doi.org/10.2533/chimia.2017.202

Keywords:

Error propagation, Model inadequacy, Quantum chemistry, Uncertainty quantification

Abstract

Computational models in chemistry rely on a number of approximations. The effect of such approximations on observables derived from them is often unpredictable. Therefore, it is challenging to quantify the uncertainty of a computational result, which, however, is necessary to assess the suitability of a computational model. Common performance statistics such as the mean absolute error are prone to failure as they do not distinguish the explainable (systematic) part of the errors from their unexplainable (random) part. In this paper, we discuss problems and solutions for performance assessment of computational models based on several examples from the quantum chemistry literature. For this purpose, we elucidate the different sources of uncertainty, the elimination of systematic errors, and the combination of individual uncertainty components to the uncertainty of a prediction.

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Published

2017-04-26

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