A Lie algebra matrix kernel method to construct equivariant permutation-invariant spaces for any connected linear Lie group, with exact dimensions and linear scaling shown for SO(3) and SU(2).
Many- body message passing for equivariant prediction of elec- tronic hamiltonians
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dm-PhiSNet predicts 1-RDMs from geometries via equivariant PhiSNet with two-stage training and analytic refinement, reducing SCF iterations 49-81% on six closed-shell molecules while giving accurate one-shot energies and forces without force supervision.
citing papers explorer
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Efficient construction of Lie group-equivariant and permutation-invariant spaces
A Lie algebra matrix kernel method to construct equivariant permutation-invariant spaces for any connected linear Lie group, with exact dimensions and linear scaling shown for SO(3) and SU(2).
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Towards Accelerated SCF Workflows with Equivariant Density-Matrix Learning and Analytic Refinement
dm-PhiSNet predicts 1-RDMs from geometries via equivariant PhiSNet with two-stage training and analytic refinement, reducing SCF iterations 49-81% on six closed-shell molecules while giving accurate one-shot energies and forces without force supervision.