pith:54HDAFAW
Fast contracted Clebsch--Gordan tensor products for equivariant graph neural networks
An O(L^3) algorithm evaluates contracted Clebsch-Gordan tensor products for O(3)-equivariant machine learning potentials using a structured grid and surface-curl pairing.
arxiv:2605.15073 v1 · 2026-05-14 · physics.comp-ph · cond-mat.mtrl-sci · physics.chem-ph
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Claims
We present an O(L^3) algorithm for evaluating contracted Clebsch--Gordan tensor products in O(3)-equivariant machine learning potentials at fixed Canonical Polyadic (CP) rank.
The structured Gauss-Legendre and Fourier grid combined with the surface-curl pairing accurately recovers all required Clebsch-Gordan channels, including antisymmetric parity-odd ones, without introducing numerical errors or breaking equivariance for the target L range.
An O(L^3) algorithm computes contracted Clebsch-Gordan tensor products for equivariant ML potentials using a structured angular grid and spherical Poisson bracket to handle parity-odd terms at fixed CP rank.
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| First computed | 2026-05-17T21:40:26.020099Z |
|---|---|
| Last reissued | 2026-05-17T21:57:19.328196Z |
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | unsigned_v0 |
| Schema | pith-number/v1.0 |
Canonical hash
ef0e3014166c895e82a41680367286489085e6560f68ba3dac95e55188660f86
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Canonical record JSON
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