activity
20202026
most citedElectronic Density Response of Warm Dense Matter

100 citations · 636 across the 31 of their papers we have counts for

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Showing 2021Show all

6 papers · 1 filter

physics.plasm-ph2021★ 37 cited

Benchmarking Exchange-Correlation Functionals in the Spin-Polarized Inhomogeneous Electron Gas under Warm Dense Conditions

Zhandos Moldabekov, Tobias Dornheim, Jan Vorberger +1

Warm dense matter is a highly active research area both at the frontier and interface of material science and plasma physics. We assess the performance of commonly used exchange-co…

physics.plasm-ph2021★ 39 cited

The Relevance of Electronic Perturbations in the Warm Dense Electron Gas

Zhandos Moldabekov, Tobias Dornheim, Maximilian Böhme +2

Warm dense matter (WDM) has emerged as one of the frontiers of both experimental and theoretical physics and is challenging traditional concepts of plasma, atomic, and condensed-ma…

physics.plasm-ph2021★ 18 cited

Thermal Signals from Collective Electronic Excitations in Inhomogeneous Warm Dense Matter

Zh. A. Moldabekov, T. Dornheim, A. Cangi

We predict the emergence of novel collective electronic excitations in warm dense matter with an inhomogeneous electronic structure based on first-principles calculations. The emer…

physics.plasm-ph2021★ 20 cited

Towards a Quantum Fluid Theory of Correlated Many-Fermion Systems from First Principles

Zh. A. Moldabekov, T. Dornheim, G. Gregori +3

Correlated many-fermion systems emerge in a broad range of phenomena in warm dense matter, plasmonics, and ultracold atoms. Quantum hydrodynamics (QHD) complements common first-pri…

physics.comp-ph2021★ 2 cited

A Machine-Learning Surrogate Model for ab initio Electronic Correlations at Extreme Conditions

Tobias Dornheim, Zhandos Moldabekov, Attila Cangi

The electronic structure in matter under extreme conditions is a challenging complex system prevalent in astrophysical objects and highly relevant for technological applications. W…

cond-mat.mtrl-sci2021★ 56 cited

Quantum-accurate magneto-elastic predictions with classical spin-lattice dynamics

Svetoslav Nikolov, Mitchell A. Wood, Attila Cangi +5

A data-driven framework is presented for building magneto-elastic machine-learning interatomic potentials (ML-IAPs) for large-scale spin-lattice dynamics simulations. The magneto-e…