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| Main Author: | |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2412.14543 |
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| _version_ | 1866915071128502272 |
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| author | van Nierop, Leo |
| author_facet | van Nierop, Leo |
| contents | In particle physics, the fundamental forces are subject to symmetries called gauge invariance. It is a redundancy in the mathematical description of any physical system. In this article I will demonstrate that the transformer architecture exhibits the same properties, and show that the default representation of transformers has partially, but not fully removed the gauge invariance. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2412_14543 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Transformer models are gauge invariant: A mathematical connection between AI and particle physics van Nierop, Leo Machine Learning High Energy Physics - Theory In particle physics, the fundamental forces are subject to symmetries called gauge invariance. It is a redundancy in the mathematical description of any physical system. In this article I will demonstrate that the transformer architecture exhibits the same properties, and show that the default representation of transformers has partially, but not fully removed the gauge invariance. |
| title | Transformer models are gauge invariant: A mathematical connection between AI and particle physics |
| topic | Machine Learning High Energy Physics - Theory |
| url | https://arxiv.org/abs/2412.14543 |