The paper introduces the first general protocol for magnetic hysteresis on programmable quantum annealers and reports non-monotonic dependence of loop area on quantum fluctuations along with disorder-induced steps.
, author Butland, J
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
verdicts
UNVERDICTED 2representative citing papers
A physics-informed CNN predicts pore-scale velocity fields from geometry and serves as a warm-start to accelerate Lattice-Boltzmann solvers in over 90% of tested cases.
citing papers explorer
-
Magnetic Hysteresis Experiments Performed on Quantum Annealers
The paper introduces the first general protocol for magnetic hysteresis on programmable quantum annealers and reports non-monotonic dependence of loop area on quantum fluctuations along with disorder-induced steps.
-
Physics-informed convolutional neural networks for fluid flow through porous media
A physics-informed CNN predicts pore-scale velocity fields from geometry and serves as a warm-start to accelerate Lattice-Boltzmann solvers in over 90% of tested cases.