Highly accurate machine learning model for kinetic energy density functional

DOI10.1016/j.physleta.2021.127621OpenAlexW3193026719MaRDI QIDQ2235652

Mohammed Alghadeer, Fahhad H. Alharbi, Abdulaziz Al-Aswad

Publication date: 21 October 2021

Published in: Physics Letters. A (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.physleta.2021.127621

zbMATH Keywords

orbital-free density functional theorykinetic energy densitylarge-scale calculationskinetic energy density functionals

Mathematics Subject Classification ID

Quantum theory (81-XX) Statistical mechanics, structure of matter (82-XX)

Cites Work

• Thomas--Fermi theory for atomic nuclei revisited
• Issues and challenges in orbital-free density functional calculations
• Bayesian Variable Selection in Linear Regression
• Semilocal Approximations for the Kinetic Energy
• Advanced Lectures on Machine Learning
• CONUNDrum: a program for orbital-free density functional theory calculations
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item

This page was built for publication: Highly accurate machine learning model for kinetic energy density functional