A U-Net-based ML pipeline reconstructs the complete phase field and quantized vortex charges in 2D Bose-Einstein condensates from density snapshots alone, using synthetic training data from projected Gross-Pitaevskii simulations.
Title resolution pending
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
years
2026 3verdicts
UNVERDICTED 3representative citing papers
A two-photon resonant process in the driven Hubbard-like model of K3C60 produces enhanced pair correlations whose resonance frequency scales downward with cluster size, supporting an electronic origin for the observed 10 THz light-induced response.
Thermalization after a quench in the Hubbard-Holstein model occurs via sharp fronts in real time and DMFT iteration space, with electron fronts appearing earlier than phonon fronts at weak coupling.
citing papers explorer
-
Machine Learning Phase Field Reconstruction in a Bose-Einstein Condensate
A U-Net-based ML pipeline reconstructs the complete phase field and quantized vortex charges in 2D Bose-Einstein condensates from density snapshots alone, using synthetic training data from projected Gross-Pitaevskii simulations.
-
Microscopic mechanism for resonant light-enhanced pair correlations in K$_3$C$_{60}$
A two-photon resonant process in the driven Hubbard-like model of K3C60 produces enhanced pair correlations whose resonance frequency scales downward with cluster size, supporting an electronic origin for the observed 10 THz light-induced response.
-
Thermalization Fronts in the Hubbard-Holstein Model
Thermalization after a quench in the Hubbard-Holstein model occurs via sharp fronts in real time and DMFT iteration space, with electron fronts appearing earlier than phonon fronts at weak coupling.