Machine learning Lie structures & applications to physics
Heng‐Yu Chen, Yang‐Hui He, Shailesh Lal, Suvajit Majumder
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 is machine-learnable, and can achieve relative speed-ups of orders of magnitude in comparison to the non-ML algorithms.
Topics & Concepts
PhysicsComputationFundamental representationSymmetry (geometry)Tensor (intrinsic definition)Lie algebraBranching (polymer chemistry)Irreducible representationTheoretical physicsAlgebra over a fieldPure mathematicsAlgorithmQuantum mechanicsWeightGeometryComputer scienceComposite materialMaterials scienceMathematicsProtein Structure and DynamicsComputational Physics and Python ApplicationsMolecular spectroscopy and chirality