Classical and exceptional Lie algebras and their representations are among the most important tools in the analysis of symmetry in physical systems. In this letter we show how the computation of tensor products and branching rules of irreducible representations is machine-learnable, and can achieve relative speed-ups of orders of magnitude in comparison to the non-ML algorithms.

中文翻译：

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机器学习谎言的结构及其在物理学中的应用

经典和特殊的李代数及其表示形式是分析物理系统对称性的最重要工具。在这封信中，我们展示了张量积和不可约表示的分支规则的计算是机器可学习的，并且与非ML算法相比，可以实现相对数量级的加速。