A step toward density benchmarking -- the energy-relevant "mean field error"

TL;DR

This paper introduces the mean-field error as a new metric to evaluate the quality of densities in density functional theory, addressing a gap in existing benchmarking methods.

Contribution

It proposes the mean-field error as a novel, reliable measure for assessing density quality, integrating it into existing error analysis frameworks.

Findings

Mean-field error effectively assesses density quality.

The measure is shown to be part of the density-driven error.

Potential for improved benchmarking protocols.

Abstract

Since the development of generalized gradient approximations in the 1990s, approximations based on density functional theory have dominated electronic structure theory calculations. Modern approximations can yield energy differences that are precise enough to be predictive in many instances, as validated by large- and small-scale benchmarking efforts. However, assessing the quality of densities has been the subject of far less attention, in part because reliable error measures are difficult to define. To this end, this work introduces the mean-field error that directly assesses the quality of densities from approximations. The mean-field error is contextualised within existing frameworks of density functional error analysis and understanding, and shown to be part of the density-driven error. It is demonstrated on several illustrative examples. Its potential use in future benchmarking protocols is discussed, and some conclusions drawn.