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Machine learning Lie structures & applications to physics

delete2021-06-01
delete14
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OA
AI
H
Heng‐Yu Chen
Y
Yang‐Hui He
S
Shailesh Lal
S
Suvajit Majumder *
DOI:10.1016/j.physletb.2021.136297delete
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Abstract

Abstract

En 中文
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. (C) 2021 The Author(s). Published by Elsevier B.V.
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Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Physics Letters B cover
Physics Letters B
IF:
4.5
Papers:
3.2W
Citations:
7.3W

Organization

N
National Taiwan University
Scholars:
4.7W
Papers: 4.2W
Citations: 3.6W
C
city st georges, university of london
Scholars:
1.2W
Papers: 1.1W
Citations: 12
N
nankai university
Scholars:
4.8W
Papers: 3.3W
Citations: 74
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