Neural networks reconstruct classical mutual information and specific entropy from limited projective measurements in the antiferromagnetic quantum Ising model, enabling reconstruction of the phase diagram even for delocalized paramagnetic states.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
verdicts
UNVERDICTED 2representative citing papers
Reviews information-based approaches for measuring physical entropy in nonequilibrium steady and absorbing states, noting their distinction from general statistical entropy estimation and their application to diverse physical systems.
citing papers explorer
-
Estimating classical mutual information between quantum subsystems with neural networks
Neural networks reconstruct classical mutual information and specific entropy from limited projective measurements in the antiferromagnetic quantum Ising model, enabling reconstruction of the phase diagram even for delocalized paramagnetic states.
-
Perspective: Measuring physical entropy out of equilibrium
Reviews information-based approaches for measuring physical entropy in nonequilibrium steady and absorbing states, noting their distinction from general statistical entropy estimation and their application to diverse physical systems.