Discovering sparse representations of Lie groups with machine learning

DOI10.1016/j.physletb.2023.138086arXiv2302.05383OpenAlexW4385075924MaRDI QIDQ6096125

Alexander Roman, Konstantin T. Matchev, Eyup B. Unlu, Sarunas Verner, Katia Matcheva, Roy T. Forestano

Publication date: 11 September 2023

Published in: Physics Letters. B (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2302.05383

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Quantum computation (81P68) Structure and representation of the Lorentz group (22E43) Lie algebras of linear algebraic groups (17B45)

Related Items (3)

Discovering sparse representations of Lie groups with machine learning ⋮ Accelerated discovery of machine-learned symmetries: deriving the exceptional Lie groups \(G_2\), \(F_4\) and \(E_6\) ⋮ Identifying the group-theoretic structure of machine-learned symmetries

Cites Work

• Machine learning Lie structures \& applications to physics
• TASI Lectures on Non-Supersymmetric BSM Models
• Discovering sparse representations of Lie groups with machine learning
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