Constrained Density Functional Theory Calculation with Iterative Optimization

TL;DR

This paper introduces an iterative optimization method for constrained density functional theory calculations that efficiently minimizes energy while optimizing Lagrange multipliers, applicable to scalar and spatially varying constraints.

Contribution

The paper presents a novel iterative approach for constrained DFT that improves efficiency and accuracy, especially for complex spatial constraints.

Findings

Method is efficient and accurate on benchmark systems.

Applicable to spatially varying constraints like charge density.

Demonstrates versatility in constrained DFT calculations.

Abstract

An iterative optimization approach that simultaneously minimizes the energy and optimizes the Lagrange multipliers enforcing desired constraints is presented. The method is tested on previously established benchmark systems and it is proved to be efficient and accurate. The approach can also be efficiently used when the constraint is not a scalar quantity but a spatially varying function like the charge density distribution.