Identifying the Group-Theoretic Structure of Machine-Learned Symmetries Article Swipe
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· 2023
· Open Access
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· DOI: https://doi.org/10.48550/arxiv.2309.07860
Deep learning was recently successfully used in deriving symmetry transformations that preserve important physics quantities. Being completely agnostic, these techniques postpone the identification of the discovered symmetries to a later stage. In this letter we propose methods for examining and identifying the group-theoretic structure of such machine-learned symmetries. We design loss functions which probe the subalgebra structure either during the deep learning stage of symmetry discovery or in a subsequent post-processing stage. We illustrate the new methods with examples from the U(n) Lie group family, obtaining the respective subalgebra decompositions. As an application to particle physics, we demonstrate the identification of the residual symmetries after the spontaneous breaking of non-Abelian gauge symmetries like SU(3) and SU(5) which are commonly used in model building.
Related Topics
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2309.07860
- https://arxiv.org/pdf/2309.07860
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4386794485
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4386794485Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.48550/arxiv.2309.07860Digital Object Identifier
- Title
-
Identifying the Group-Theoretic Structure of Machine-Learned SymmetriesWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
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2023-09-14Full publication date if available
- Authors
-
Roy T. Forestano, K. Matchev, Katia Matcheva, Alexander Roman, Eyup B. Unlu, Sarunas VernerList of authors in order
- Landing page
-
https://arxiv.org/abs/2309.07860Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2309.07860Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2309.07860Direct OA link when available
- Concepts
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Homogeneous space, Subalgebra, Abelian group, Group (periodic table), Symmetry (geometry), Lie group, Symmetry group, Identification (biology), Computer science, Pure mathematics, Theoretical physics, Spacetime symmetries, Artificial intelligence, Algebra over a field, Physics, Theoretical computer science, Mathematics, Quantum mechanics, Geometry, Quantum, Quantum field theory in curved spacetime, Biology, Quantum gravity, BotanyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.used | 5, 119 |
| abstract_inverted_index.with | 77 |
| abstract_inverted_index.Being | 15 |
| abstract_inverted_index.SU(3) | 113 |
| abstract_inverted_index.SU(5) | 115 |
| abstract_inverted_index.after | 104 |
| abstract_inverted_index.gauge | 110 |
| abstract_inverted_index.group | 83 |
| abstract_inverted_index.later | 29 |
| abstract_inverted_index.model | 121 |
| abstract_inverted_index.probe | 53 |
| abstract_inverted_index.stage | 62 |
| abstract_inverted_index.these | 18 |
| abstract_inverted_index.which | 52, 116 |
| abstract_inverted_index.design | 49 |
| abstract_inverted_index.during | 58 |
| abstract_inverted_index.either | 57 |
| abstract_inverted_index.letter | 33 |
| abstract_inverted_index.stage. | 30, 71 |
| abstract_inverted_index.family, | 84 |
| abstract_inverted_index.methods | 36, 76 |
| abstract_inverted_index.physics | 13 |
| abstract_inverted_index.propose | 35 |
| abstract_inverted_index.breaking | 107 |
| abstract_inverted_index.commonly | 118 |
| abstract_inverted_index.deriving | 7 |
| abstract_inverted_index.examples | 78 |
| abstract_inverted_index.learning | 1, 61 |
| abstract_inverted_index.particle | 94 |
| abstract_inverted_index.physics, | 95 |
| abstract_inverted_index.postpone | 20 |
| abstract_inverted_index.preserve | 11 |
| abstract_inverted_index.recently | 3 |
| abstract_inverted_index.residual | 102 |
| abstract_inverted_index.symmetry | 8, 64 |
| abstract_inverted_index.agnostic, | 17 |
| abstract_inverted_index.building. | 122 |
| abstract_inverted_index.discovery | 65 |
| abstract_inverted_index.examining | 38 |
| abstract_inverted_index.functions | 51 |
| abstract_inverted_index.important | 12 |
| abstract_inverted_index.obtaining | 85 |
| abstract_inverted_index.structure | 43, 56 |
| abstract_inverted_index.completely | 16 |
| abstract_inverted_index.discovered | 25 |
| abstract_inverted_index.illustrate | 73 |
| abstract_inverted_index.respective | 87 |
| abstract_inverted_index.subalgebra | 55, 88 |
| abstract_inverted_index.subsequent | 69 |
| abstract_inverted_index.symmetries | 26, 103, 111 |
| abstract_inverted_index.techniques | 19 |
| abstract_inverted_index.application | 92 |
| abstract_inverted_index.demonstrate | 97 |
| abstract_inverted_index.identifying | 40 |
| abstract_inverted_index.non-Abelian | 109 |
| abstract_inverted_index.quantities. | 14 |
| abstract_inverted_index.spontaneous | 106 |
| abstract_inverted_index.symmetries. | 47 |
| abstract_inverted_index.successfully | 4 |
| abstract_inverted_index.identification | 22, 99 |
| abstract_inverted_index.decompositions. | 89 |
| abstract_inverted_index.group-theoretic | 42 |
| abstract_inverted_index.machine-learned | 46 |
| abstract_inverted_index.post-processing | 70 |
| abstract_inverted_index.transformations | 9 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 6 |
| citation_normalized_percentile |