We propose a theoretical/computational protocol based on the use of the Ground State Path Integral Quantum Monte Carlo for the calculation of the kinetic and Coulomb energy density for a system of N interacting electrons in an external potential. The idea is based on the derivation of the energy densities via the (N − 1)-conditional probability density within the framework of the Levy–Lieb constrained search principle. The consequences for the development of energy functionals within the context of density functional theory are discussed. We propose also the possibility of going beyond the energy densities and extend this idea to a computational procedure where the (N − 1)-conditional probability is an implicit functional of the electron de...
An iterative algorithm for simultaneous determination of the ground-state electron chemical potentia...
In this paper we explore new ways to study the zero temperature limit of quantum statistical mechani...
Quantum Monte Carlo methods are among the most accurate algorithms for predicting properties of gene...
We propose a theoretical/computational protocol based on the use of the Ground State Path Integral Q...
We review an approach where the energy functional of Density-Functional Theory (DFT) can be determin...
Abstract We review an approach where the energy functional of Density-Functional Theory (DFT) can be...
The density matrix theory, the ancestor of density functional theory, provides the immediate framewo...
In this paper we explore ways to study the zero temperature limit of quantum statistical mechanics u...
We consider a gas of interacting electrons in the limit of nearly uniform density and treat the one ...
We consider a gas of interacting electrons in the limit of nearly uniform density and treat the one ...
The work in this thesis is aimed, broadly speaking, at developing methods of applying quantum mechan...
We present conditional probability (CP) density functional theory (DFT) as a formally exact theory. ...
Starting from an exact lower bound on the imaginary-time propagator, we present a path-integral quan...
We present an alternative to the Kohn-Sham formulation of density-functional theory for the ground-s...
The auxiliary‐field quantum Monte Carlo (AFQMC) method provides a computational framework for solvin...
An iterative algorithm for simultaneous determination of the ground-state electron chemical potentia...
In this paper we explore new ways to study the zero temperature limit of quantum statistical mechani...
Quantum Monte Carlo methods are among the most accurate algorithms for predicting properties of gene...
We propose a theoretical/computational protocol based on the use of the Ground State Path Integral Q...
We review an approach where the energy functional of Density-Functional Theory (DFT) can be determin...
Abstract We review an approach where the energy functional of Density-Functional Theory (DFT) can be...
The density matrix theory, the ancestor of density functional theory, provides the immediate framewo...
In this paper we explore ways to study the zero temperature limit of quantum statistical mechanics u...
We consider a gas of interacting electrons in the limit of nearly uniform density and treat the one ...
We consider a gas of interacting electrons in the limit of nearly uniform density and treat the one ...
The work in this thesis is aimed, broadly speaking, at developing methods of applying quantum mechan...
We present conditional probability (CP) density functional theory (DFT) as a formally exact theory. ...
Starting from an exact lower bound on the imaginary-time propagator, we present a path-integral quan...
We present an alternative to the Kohn-Sham formulation of density-functional theory for the ground-s...
The auxiliary‐field quantum Monte Carlo (AFQMC) method provides a computational framework for solvin...
An iterative algorithm for simultaneous determination of the ground-state electron chemical potentia...
In this paper we explore new ways to study the zero temperature limit of quantum statistical mechani...
Quantum Monte Carlo methods are among the most accurate algorithms for predicting properties of gene...