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Integral Formulas for Vector Spherical Tensor Products

Machine Learning 2026-03-10 v1 Computational Physics

Abstract

We derive integral formulas that simplify the Vector Spherical Tensor Product recently introduced by Xie et al., which generalizes the Gaunt tensor product to antisymmetric couplings. In particular, we obtain explicit closed-form expressions for the antisymmetric analogues of the Gaunt coefficients. This enables us to simulate the Clebsch-Gordan tensor product using a single Vector Spherical Tensor Product, yielding a 9×9\times reduction in the required tensor product evaluations. Our results enable efficient and practical implementations of the Vector Spherical Tensor Product, paving the way for applications of this generalization of Gaunt tensor products in SO(3)\mathrm{SO}(3)-equivariant neural networks. Moreover, we discuss how the Gaunt and the Vector Spherical 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.

Cite

@article{arxiv.2603.08630,
  title  = {Integral Formulas for Vector Spherical Tensor Products},
  author = {Valentin Heyraud and Zachary Weller-Davies and Jules Tilly},
  journal= {arXiv preprint arXiv:2603.08630},
  year   = {2026}
}

Comments

16 pages, 2 figures

R2 v1 2026-07-01T11:10:42.749Z