A tensor network algorithm computes momentum-resolved spectral functions for large non-periodic super-moiré systems by mapping tight-binding problems to solvable quantum many-body simulations using kernel polynomial methods and quantum Fourier transforms.
Title resolution pending
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
citation-role summary
method 1
citation-polarity summary
fields
cond-mat.str-el 3roles
method 1polarities
use method 1representative citing papers
Generalized ML force fields reproduce non-collinear magnetic orders on lattices and predict voltage-driven domain-wall motion in itinerant magnets using extensions to nonequilibrium torques.
Cumulant expansion in the independent-particle approximation accurately calculates charge mobility for weak to moderate electron-phonon coupling in Peierls and Fröhlich models, as validated against Boltzmann and Migdal approaches.
citing papers explorer
-
Tensor network approach to momentum-resolved spectroscopy in non-periodic super-moir\'e systems
A tensor network algorithm computes momentum-resolved spectral functions for large non-periodic super-moiré systems by mapping tight-binding problems to solvable quantum many-body simulations using kernel polynomial methods and quantum Fourier transforms.
-
Machine-learning modeling of magnetization dynamics in quasi-equilibrium and driven metallic spin systems
Generalized ML force fields reproduce non-collinear magnetic orders on lattices and predict voltage-driven domain-wall motion in itinerant magnets using extensions to nonequilibrium torques.
-
Applicability of the cumulant expansion method for the calculation of transport properties in electron-phonon systems
Cumulant expansion in the independent-particle approximation accurately calculates charge mobility for weak to moderate electron-phonon coupling in Peierls and Fröhlich models, as validated against Boltzmann and Migdal approaches.