With the growth of computational resources, the scope of electronic structure simulations has
increased greatly. Artificial intelligence and robust data analysis hold the promise to …

Machine learning (ML) is an increasingly popular statistical tool for analyzing either
measured or calculated data sets. Here, we explore its application to a well‐defined physics …

Orbital-free density functional theory (OFDFT) is a quantum chemistry formulation that has a
lower cost scaling than the prevailing Kohn–Sham DFT, which is increasingly desired for …

A simple, unconventional, nonempirical, constraint-based orbital-free generalized gradient
approximation (GGA) noninteracting kinetic energy density functional is presented along …

Kinetic energy (KE) approximations are key elements in orbital-free density functional
theory. To date, the use of nonlocal functionals, possibly employing system-dependent …

We introduce a practical hybrid approach that combines orbital-free density functional theory
(DFT) with Kohn-Sham DFT for speeding up first-principles molecular dynamics simulations …

Differentiable programming has facilitated numerous methodological advances in scientific
computing. Physics engines supporting automatic differentiation have simpler code …

We explore the simplification of widely used meta-generalized-gradient approximation
(mGGA) exchange-correlation functionals to the Laplacian level of refinement by use of …

This work extends the orbital-free density functional theory to the field of quantum
crystallography. The total electronic energy is decomposed into electrostatic, exchange …

In this article, I will discuss the overlap between the concept of Shannon entropy and the
concept of electronic correlation. Quantum Monte Carlo numerical results for the uniform …