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Machine learning the derivative discontinuity of density-functional theory
Johannes Gedeon, Jonathan Schmidt, Matthew J. P. Hodgson +3
Machine learning is a powerful tool to design accurate, highly non-local, exchange-correlation functionals for density functional theory. So far, most of those machine learned func…
Meta-local density functionals: a new rung on Jacob's ladder
Susi Lehtola, Miguel A. L. Marques
The homogeneous electron gas (HEG) is a key ingredient in the construction of most exchange-correlation functionals of density-functional theory. Often, the energy of the HEG is pa…
Iodine molecule modifications with high pressure
Jingming Shi, Emiliano Fonda, Silvana Botti +8
Metallization and dissociation are key transformations in diatomic molecules at high densities particularly significant for modeling giant planets. Using X-ray absorption spectrosc…
Towards a formal definition of static and dynamic electronic correlations
Carlos L. Benavides-Riveros, Nektarios N. Lathiotakis, Miguel A. L. Marques
Some of the most spectacular failures of density-functional and Hartree-Fock theories are related to an incorrect description of the so-called static electron correlation. Motivate…
Generalized Pauli constraints in reduced density matrix functional theory
Iris Theophilou, Nektarios N. Lathiotakis, Miguel A. L. Marques +1
Functionals of the one-body reduced density matrix (1-RDM) are routinely minimized under Coleman's ensemble -representability conditions. Recently, the topic of pure-state -r…
Real-space grids and the Octopus code as tools for the development of new simulation approaches for electronic systems
Xavier Andrade, David A. Strubbe, Umberto De Giovannini +13
Real-space grids are a powerful alternative for the simulation of electronic systems. One of the main advantages of the approach is the flexibility and simplicity of working direct…