Deep learning symmetries and their Lie groups, algebras, and subalgebras from first principles

Deep learning symmetries and their Lie groups, algebras, and subalgebras from first principles

We design a deep-learning algorithm for the discovery and identification of the continuous group of symmetries present in a labeled dataset. We use fully connected neural networks to model the symmetry transformations and the corresponding generators. The constructed loss functions ensure that the a...

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Bibliographic Details
Main Authors: Roy T Forestano, Konstantin T Matchev, Katia Matcheva, Alexander Roman, Eyup B Unlu, Sarunas Verner
Format: Article
Language:English
Published: IOP Publishing 2023-01-01
Series:Machine Learning: Science and Technology
Subjects:
symmetries
subalgebras
machine-learning
Lorentz group
Lie algebras
supervised learning
Online Access:https://doi.org/10.1088/2632-2153/acd989

Internet

https://doi.org/10.1088/2632-2153/acd989

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