Integral Formulas for Vector Signal Tensor Products
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Abstract (arXiv)
We derive integral formulas that simplify the Vector Signal Tensor Product recently introduced by Xie et al., which generalizes the Gaunt tensor product to anti-symmetric couplings. In particular, we obtain explicit closed-form expressions for the anti-symmetric analogues of the Gaunt coefficients. This enables us to simulate the Clebsch-Gordan tensor product using a single Vector Signal Tensor Product, yielding up to a 9× reduction in the required tensor product evaluations. Our results enable efficient and practical implementations of the Vector Signal Tensor Product, paving the way for applications of this generalization of Gaunt Tensor Products in SO(3)-equivariant neural networks. Moreover, we discuss how the Gaunt and the Vector Signal Tensor Products allow to control the expressivity-runtime tradeoff associated with the usual Clebsch-Gordan Tensor Products. Finally, we investigate low rank decompositions of the normalizations of the considered tensor products in view of their use in equivariant neural networks.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 7 of its 16 references that are in the map. First posted on arXiv 9 Mar 2026.
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7 of 16 references.
References · 7
- 2022MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fieldscited by 474
- 2023Reducing SO(3) Convolutions to SO(2) for Efficient Equivariant GNNscited by 117
- 2024Enabling Efficient Equivariant Operations in the Fourier Basis via Gaunt Tensor Productscited by 36
- 2025The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Productscited by 15
- 2025E2Former: An Efficient and Equivariant Transformer with Linear-Scaling Tensor Productscited by 12
- 2023Differentiable and accelerated spherical harmonic and Wigner transformscited by 6
- 2026Asymptotically Fast Clebsch-Gordan Tensor Products with Vector Spherical Harmonicscited by 4
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Citing papers per year: 2026: 1.
1 paper.