Machine Learning Lie Structures & Applications to Physics
arXiv:2011.00871 · doi:10.1016/j.physletb.2021.136297
Abstract
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 are machine-learnable, and can achieve relative speed-ups of orders of magnitude in comparison to the non-ML algorithms.
6 pages, 7 figures
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