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WTMAD-4: a fair weighting scheme for GMTKN55.

Kyle R Bryenton1,2, Erin R Johnson1,2,3

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A flaw in standard performance metrics for molecular quantum chemistry benchmarks was identified. A new WTMAD-4 metric ensures fair evaluation of electronic-structure methods, improving accuracy for density-functional approximations.

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Area of Science:

  • Molecular quantum chemistry
  • Computational chemistry
  • Electronic structure theory

Background:

  • The GMTKN55 dataset is a standard benchmark for evaluating electronic-structure methods in molecular quantum chemistry.
  • Current performance metrics, like weighted mean absolute deviation (WTMAD), unfairly under-weight certain benchmarks within the GMTKN55 set.
  • This can lead to inaccurate assessments of method performance, particularly for density-functional approximations (DFAs).

Purpose of the Study:

  • To identify and address the flaw in existing WTMAD definitions used for the GMTKN55 dataset.
  • To propose a new, more equitable performance metric (WTMAD-4) that properly accounts for all component benchmarks.
  • To reassess the performance of a large number of DFAs using the improved metric.

Main Methods:

  • Analysis of existing WTMAD definitions and their impact on GMTKN55 benchmark weighting.
  • Development of the WTMAD-4 metric, calibrated using errors from ten minimally empirical dispersion-corrected DFAs.
  • Reassessment of 115 DFAs using the WTMAD-4 metric.

Main Results:

  • A significant under-weighting of certain GMTKN55 benchmarks by conventional WTMAD definitions was confirmed.
  • The proposed WTMAD-4 metric provides a more balanced and fair evaluation across all GMTKN55 benchmarks.
  • Reassessment revealed instances where DFAs optimized with WTMAD-2 show suboptimal performance on benchmarks marginalized by that metric.

Conclusions:

  • The WTMAD-4 metric offers a more reliable way to assess electronic-structure method performance on the GMTKN55 dataset.
  • Fairer evaluation is crucial for developing accurate and robust density-functional approximations.
  • Existing optimization strategies may need revision to account for the limitations of older WTMAD metrics.