A time-dependent partial density of states is defined and computed for laser-driven materials, illustrated on wurtzite ZnO to reveal bond structure in the dressed electron density.
Title resolution pending
4 Pith papers cite this work. Polarity classification is still indexing.
4
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
verdicts
UNVERDICTED 4roles
background 1polarities
background 1representative citing papers
YbN thin films are insulating with a 1.7 eV band gap, showing LO and TO phonon modes plus a defect-induced absorption tail indicating the Fermi level lies in a disordered conduction band minimum.
A shallow restricted Boltzmann machine variational Monte Carlo ansatz reproduces the main features of the adiabatic phase diagram and selected symmetry-broken insulating states for the one-dimensional Z2 Bose-Hubbard chain at half filling.
Krylov subspace methods efficiently describe quantum evolution, operator growth, and chaos in many-body systems, with metrics like Krylov complexity and applications in open systems, QFT, and quantum computing.
citing papers explorer
-
Laser-dressed partial density of states
A time-dependent partial density of states is defined and computed for laser-driven materials, illustrated on wurtzite ZnO to reveal bond structure in the dressed electron density.
-
Optical, vibrational, and electronic properties of semiconducting YbN
YbN thin films are insulating with a 1.7 eV band gap, showing LO and TO phonon modes plus a defect-induced absorption tail indicating the Fermi level lies in a disordered conduction band minimum.
-
Benchmarking a restricted Boltzmann machine on the $\mathbb{Z}_2$ Bose-Hubbard chain in the adiabatic hard-core regime
A shallow restricted Boltzmann machine variational Monte Carlo ansatz reproduces the main features of the adiabatic phase diagram and selected symmetry-broken insulating states for the one-dimensional Z2 Bose-Hubbard chain at half filling.
-
Quantum Dynamics in Krylov Space: Methods and Applications
Krylov subspace methods efficiently describe quantum evolution, operator growth, and chaos in many-body systems, with metrics like Krylov complexity and applications in open systems, QFT, and quantum computing.