Rediscovery of Numerical Lüscher's Formula from the Neural Network
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arXiv
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| Hauptverfasser: | , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2022
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| _version_ | 1866929304257953792 |
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| author | Lu, Yu Wang, Yi-Jia Chen, Ying Wu, Jia-Jun |
| author_facet | Lu, Yu Wang, Yi-Jia Chen, Ying Wu, Jia-Jun |
| contents | We present that by predicting the spectrum in discrete space from the phase shift in continuous space, the neural network can remarkably reproduce the numerical Lüscher's formula to a high precision. The model-independent property of the Lüscher's formula is naturally realized by the generalizability of the neural network. This exhibits the great potential of the neural network to extract model-independent relation between model-dependent quantities, and this data-driven approach could greatly facilitate the discovery of the physical principles underneath the intricate data. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2210_02184 |
| institution | arXiv |
| publishDate | 2022 |
| record_format | arxiv |
| spellingShingle | Rediscovery of Numerical Lüscher's Formula from the Neural Network Lu, Yu Wang, Yi-Jia Chen, Ying Wu, Jia-Jun High Energy Physics - Lattice Machine Learning High Energy Physics - Phenomenology High Energy Physics - Theory We present that by predicting the spectrum in discrete space from the phase shift in continuous space, the neural network can remarkably reproduce the numerical Lüscher's formula to a high precision. The model-independent property of the Lüscher's formula is naturally realized by the generalizability of the neural network. This exhibits the great potential of the neural network to extract model-independent relation between model-dependent quantities, and this data-driven approach could greatly facilitate the discovery of the physical principles underneath the intricate data. |
| title | Rediscovery of Numerical Lüscher's Formula from the Neural Network |
| topic | High Energy Physics - Lattice Machine Learning High Energy Physics - Phenomenology High Energy Physics - Theory |
| url | https://arxiv.org/abs/2210.02184 |