# Computing the Self-Consistent Field in Kohn-Sham Density Functional Theory

## TL;DR

This paper introduces a new framework for evaluating and improving the convergence of self-consistent field methods in Kohn-Sham density functional theory, including a benchmark suite for algorithm comparison.

## Contribution

It presents a novel framework and benchmark suite for assessing the performance and stability of self-consistent field algorithms in Kohn-Sham DFT.

## Key findings

- Identifies sources of inefficiency and instability in SCF iterations.
- Provides methods to mitigate convergence difficulties.
- Offers a comprehensive benchmark suite for algorithm evaluation.

## Abstract

A new framework is presented for evaluating the performance of self-consistent field methods in Kohn-Sham density functional theory. The aims of this work are two-fold. First, we explore the properties of Kohn-Sham density functional theory as it pertains to the convergence of self-consistent field iterations. Sources of inefficiencies and instabilities are identified, and methods to mitigate these difficulties are discussed. Second, we introduce a framework to assess the relative utility of algorithms in the present context, comprising a representative benchmark suite of over fifty Kohn-Sham simulation inputs, the \textsc{scf}-$x_n$ suite. This provides a new tool to develop, evaluate and compare new algorithms in a fair, well-defined and transparent manner.