Studying number theory with deep learning: a case study with the Möbius and squarefree indicator functions
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arXiv
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866909705826205696 |
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| author | Lowry-Duda, David |
| author_facet | Lowry-Duda, David |
| contents | Building on work of Charton, we train small transformer models to calculate the Möbius function $μ(n)$ and the squarefree indicator function $μ^2(n)$. The models attain nontrivial predictive power. We apply a mixture of additional models and feature scoring to give a theoretical explanation. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_10335 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Studying number theory with deep learning: a case study with the Möbius and squarefree indicator functions Lowry-Duda, David Number Theory Machine Learning Building on work of Charton, we train small transformer models to calculate the Möbius function $μ(n)$ and the squarefree indicator function $μ^2(n)$. The models attain nontrivial predictive power. We apply a mixture of additional models and feature scoring to give a theoretical explanation. |
| title | Studying number theory with deep learning: a case study with the Möbius and squarefree indicator functions |
| topic | Number Theory Machine Learning |
| url | https://arxiv.org/abs/2502.10335 |