Equivariant neural networks for 2D Q-tensor prediction in nematic liquid crystals achieve lower errors and better generalization than non-equivariant models while satisfying symmetry constraints.
Bekkers, Maxime W
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cond-mat.soft 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
On the Equivariant Learning of the $Q$-tensor Order Parameter
Equivariant neural networks for 2D Q-tensor prediction in nematic liquid crystals achieve lower errors and better generalization than non-equivariant models while satisfying symmetry constraints.